1. |
- Liang, Yuli, 1985-, et al.
(author)
-
On estimation in multilevel models with block circular symmetric covariance structure
- 2012
-
In: Acta et Commentationes Universitatis Tartuensis de Mathematica. - Tartu : University of Tartu Press. - 1406-2283 .- 2228-4699. ; 16:1, s. 83-96
-
Journal article (peer-reviewed)abstract
- In this article we consider a multilevel model with block circular symmetric covariance structure. Maximum likelihood estimation of the parameters of this model is discussed. We show that explicit maximum likelihood estimators of variance components exist under certain restrictions on the parameter space.
|
|
2. |
- Aad, G., et al.
(author)
-
- 2012
-
swepub:Mat__t (peer-reviewed)
|
|
3. |
- Ahmed, S. Ejaz, et al.
(author)
-
Estimation of Several Intraclass Correlation Coefficients
- 2015
-
In: Communications in statistics. Simulation and computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 44:9, s. 2315-2328
-
Journal article (peer-reviewed)abstract
- An intraclass correlation coefficient observed in several populations is estimated. The basis is a variance-stabilizing transformation. It is shown that the intraclass correlation coefficient from any elliptical distribution should be transformed in the same way. Four estimators are compared. An estimator where the components in a vector consisting of the transformed intraclass correlation coefficients are estimated separately, an estimator based on a weighted average of these components, a pretest estimator where the equality of the components is tested and then the outcome of the test is used in the estimation procedure, and a James-Stein estimator which shrinks toward the mean.
|
|
4. |
- Hao, Chengcheng, 1986-
(author)
-
Explicit Influence Analysis in Crossover Models
- 2014
-
Doctoral thesis (other academic/artistic)abstract
- This dissertation develops influence diagnostics for crossover models. Mixed linear models and generalised mixed linear models are utilised to investigate continuous and count data from crossover studies, respectively.For both types of models, changes in the maximum likelihood estimates of parameters, particularly in the estimated treatment effect, due to minor perturbations of the observed data, are assessed. The novelty of this dissertation lies in the analytical derivation of influence diagnostics using decompositions of the perturbed mixed models. Consequently, the suggested influence diagnostics, referred to as the delta-beta and variance-ratio influences, provide new findings about how the constructed residuals affect the estimation in terms of different parameters of interest.The delta-beta and variance-ratio influence in three different crossover models are studied in Chapters 5-6, respectively. Chapter 5 analyses the influence of subjects in a two-period continuous crossover model. Possible problems with observation-level perturbations in crossover models are discussed. Chapter 6 extends the approach to higher-order crossover models. Furthermore, not only the individual delta-beta and variance-ratio influences of a subject are derived, but also the joint influences of two subjects from different sequences. Chapters 5-6 show that the delta-beta and variance-ratio influences of a particular parameter are decided by the special linear combination of the constructed residuals. In Chapter 7, explicit delta-beta influence on the estimated treatment effect in the two-period count crossover model is derived. The influence is related to the Pearson residuals of the subject. Graphical tools are developed to visualise information of influence concerning crossover models for both continuous and count data. Illustrative examples are provided in each chapter.
|
|
5. |
- Hao, Chengcheng, 1986-, et al.
(author)
-
Explicit Influence Analysis in Two-Treatment Balanced Crossover Models
- 2015
-
In: Mathematical Methods of Statistics. - New York, NY, United States : Allerton Press, Inc.. - 1066-5307 .- 1934-8045. ; 24:1, s. 16-36
-
Journal article (peer-reviewed)abstract
- This paper considers how to detect influential observations in crossover models with random individual effects. Two influence measures, the delta-beta influence and variance-ratio influence, are utilized as tools to evaluate the influence of the model on the estimates of mean and variance parameters with respect to case-weighted perturbations, which are introduced to the model for studying the ‘influence’ of cases. The paper provides explicit expressions of the delta-beta and variance-ratio influences for the general two-treatment balanced crossover models when the proposed decompositions for the perturbed models hold. The influence measures for each parameter turn out to be closed-form functions of orthogonal projections of specific residuals in the unperturbed model.
|
|
6. |
- Hao, Chengcheng, et al.
(author)
-
Influence analysis in two-treatment cross-over designs with special reference to the ABBA|BAAB design
- 2011
-
Reports (other academic/artistic)abstract
- This work is to develop methodology to detect influential observations in linear mixed model for multiple-period two-treatment cross-over designs. Existence of explicit maximum likelihood estimates (MLEs) of variance parameters as well as of mean parameters in the mixed model with treatment, residual, period and sequence effects is proven. Special reference is taken to the four-period ABBA|BAAB design. Case-weighted perturbations are performed. The influence quantities on each parameter estimate and their dispersion matrix are presented as closed-form functions of residuals in the unperturbed model.
|
|
7. |
- Hao, Chengcheng, 1986-, et al.
(author)
-
Influence diagnostics for count data under AB-BA crossover trials
- 2017
-
In: Statistical Methods in Medical Research. - : SAGE Publications. - 0962-2802 .- 1477-0334. ; 26:6, s. 2938-2950
-
Journal article (peer-reviewed)abstract
- This paper aims to develop diagnostic measures to assess the influence of data perturbations on estimates in AB-BA crossover studies with a Poisson distributed response. Generalised mixed linear models with normally distributed random effects are utilised. We show that in this special case, the model can be decomposed into two independent sub-models which allow to derive closed-form expressions to evaluate the changes in the maximum likelihood estimates under several perturbation schemes. The performance of the new influence measures is illustrated by simulation studies and the analysis of a real dataset.
|
|
8. |
- Hao, Chengcheng, 1986-
(author)
-
Local Influence Analysis and Cross-over Studies
- 2011
-
Licentiate thesis (other academic/artistic)abstract
- With a special reference to cross-over design models with random individual effects, the purpose of this dissertation is to develop new methodology to detect influential observations in the context of mixed linear models with explicit maximum likelihood estimators (MLEs).Case-weighted perturbation schemes within and between subjects in mixed models are constructed. It is emphasised that perturbations should be performed under the restriction that explicit MLEs can be obtained in the perturbed model. Two influence functions, the delta-beta influence and variance-ratio influence, are tools to evaluate the influence on the estimates of mean parameters and variance parameters, respectively, with respect to the used perturbations.The proposed approach, named the delta-beta-based local influence approach, derives the expressions of the delta-beta and variance-ratio influences for two specific cross-over designs. In both the AB|BA design (2 X 2 cross-over design) and the ABBA|BAAB design, the applied influence functions turn out to have closed-form expressions of residuals from the unperturbed models. Some graphical tools are also presented.
|
|
9. |
- Hao, Chengcheng, et al.
(author)
-
Local influence analysis in 2 X 2 cross-over designs
- 2011
-
Reports (other academic/artistic)abstract
- The aim of this work is to develop new methodology to detect influential observations in cross-over design models with random individual effects. Various case-weighted perturbations are performed. We derive the exact solution of influence of the perturbations on each parameter estimate and their dispersion matrix. Closed-form maximum likelihood estimates (MLEs) of variance parameters as well as fixed effect parameters in the cross-over design models are utilised. The work exhibits the possibility to produce closed-form expressions of the influence using the residuals in mixed models. A discussion on restrictions of the case-weighted perturbation schemes is given. Some graphical tools are also presented.
|
|
10. |
- Hao, Chengcheng, et al.
(author)
-
Local Influence Analysis in AB–BA Crossover Designs
- 2014
-
In: Scandinavian Journal of Statistics. - : Wiley. - 0303-6898 .- 1467-9469. ; 41:4, s. 1153-1166
-
Journal article (peer-reviewed)abstract
- The aim of this article is to develop methodology for detecting influential observations in crossover models with random individual effects. Various case-weighted perturbations are performed. We obtain the influence of the perturbations on each parameter estimator and on their dispersion matrices. The obtained results exhibit the possibility to obtain closed-form expressions of the influence using the residuals in mixed linear models. Some graphical tools are also presented.
|
|
11. |
- Kollo, Tõnu, et al.
(author)
-
Estimation in high-dimensional analysis and multivariate linear models
- 2008
-
Reports (other academic/artistic)abstract
- When the number of variables compared with the number of observationsis large this paper presents a new approach of estimating the parametersdescribing the mean structure in the Growth Curve model. An explicitestimator is obtained which is unbiased, consistent and asymptoticallynormally distributed. Its variance is also derived.
|
|
12. |
- Kollo, Tõnu, et al.
(author)
-
Estimation in high-dimensional analysis and multivariate linear models
- 2011
-
In: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 40:7, s. 1241-1253
-
Journal article (peer-reviewed)abstract
- This article presents a new approach of estimating the parameters describing the mean structure in the Growth Curve model when the number of variables compared with the number of observations is large.
|
|
13. |
- Liang, Yuli, 1985-
(author)
-
A study of multilevel models with block circular symmetric covariance structures
- 2011
-
Licentiate thesis (other academic/artistic)abstract
- This thesis concerns the study of multilevel models with specific patterned covariance structures and addresses the issues of maximum likelihoodestimation. In particular, circular symmetric hierarchical datastructures are considered.In the first paper (Paper I), we consider so-called dihedral block symmetrymodels and extend them to models which covariance structures reflects both circularity and exchangeability present in the data. The main contribution of Paper I are two derived patterns of the covariancematrices which characterizes models under consideration. The relationship between these two patterned covariance matrices was investigatedand it has been verified they are similar matrices. New expressions for the eigenvalues of block circular symmetric matrices are obtained which take into account the block structure. Paper II deals with estimation ofbalanced multilevel models with block circular symmetric covariance matrices. The spectral properties of such patterned covariance matrices are established. Maximum likelihood estimation is considered through the spectral decomposition of the patterned covariance matrix. The main results of Paper II concern the spectrum of the covariance matrix inthe model of interest and the existence of explicit maximum likelihood estimators for the covariance parameters.
|
|
14. |
- Liang, Yuli, 1985-, et al.
(author)
-
Block Circular Symmetry in Multilevel Models
- 2011
-
Reports (other academic/artistic)abstract
- Models that describe symmetries present in the error structure of observations have been widely used in dierent applications, with early examples from psychometric and medical research. The aim of this article is to study a multilevel model with a covariance structure that is block circular symmetric. Useful results are obtained for the spectra of these structured matrices.
|
|
15. |
- Liang, Yuli, 1985-
(author)
-
Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
- 2015
-
Doctoral thesis (other academic/artistic)abstract
- This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously.We derive two covariance structures under two different invariance restrictions. The obtained covariance structures reflect both circularity and exchangeability present in the data. In particular, estimation in the balanced random effects with block circular covariance matrices is considered. The spectral properties of such patterned covariance matrices are provided. Maximum likelihood estimation is performed through the spectral decomposition of the patterned covariance matrices. Existence of the explicit maximum likelihood estimators is discussed and sufficient conditions for obtaining explicit and unique estimators for the variance-covariance components are derived. Different restricted models are discussed and the corresponding maximum likelihood estimators are presented.This thesis also deals with hypothesis testing of block covariance structures, especially block circular Toeplitz covariance matrices. We consider both so-called external tests and internal tests. In the external tests, various hypotheses about testing block covariance structures, as well as mean structures, are considered, and the internal tests are concerned with testing specific covariance parameters given the block circular Toeplitz structure. Likelihood ratio tests are constructed, and the null distributions of the corresponding test statistics are derived.
|
|
16. |
- Liang, Yuli, 1985-, et al.
(author)
-
Estimation in multilevel models with block circular symmetric covariance structure
- 2011
-
Reports (other academic/artistic)abstract
- In this article we consider a multilevel model with block circular symmetric covariance structure. Maximum likelihood estimation of the parameters of this model is discussed. We show that explicit maximum likelihood estimators of variance components exist under certain restrictions on the parameter space.
|
|
17. |
- Liang, Yuli, et al.
(author)
-
Hierarchical Models with Block Circular Covariance Structures
- 2013
-
Reports (other academic/artistic)abstract
- Hierarchical linear models with a block circular covariance structure are considered. Sufficient conditions for obtaining explicit and unique estimators for the variance-covariance components are derived. Different restricted models are discussed and maximum likelihood estimators are presented.
|
|
18. |
- Liang, Yuli, 1985-, et al.
(author)
-
On estimation in hierarchical models with block circular covariance structures
- 2015
-
In: Annals of the Institute of Statistical Mathematics. - : Springer. - 0020-3157 .- 1572-9052. ; 67:4, s. 773-791
-
Journal article (peer-reviewed)abstract
- Hierarchical linear models with a block circular covariance structure are considered. Sufficient conditions for obtaining explicit and unique estimators for the variance-covariance components are derived. Different restricted models are discussed and maximum likelihood estimators are presented. The theory is illustrated through covariance matrices of small sizes and a real-life example.
|
|
19. |
- Liang, Yuli, 1985-, et al.
(author)
-
On properties of Toeplitz-type covariance matrices in models with nested random effects
- 2021
-
In: Statistical papers. - : Springer. - 0932-5026 .- 1613-9798. ; 62:6, s. 2509-2528
-
Journal article (peer-reviewed)abstract
- Models that capture symmetries present in the data have been widely used in different applications, with early examples from psychometric and medical research. The aim of this article is to study a random effects model focusing on the covariance structure that is block circular symmetric. Useful results are obtained for the spectra of these structured matrices.
|
|
20. |
- Liang, Yuli, 1985-, et al.
(author)
-
Testing in multivariate normal models with block circular covariance structures
- 2015
-
Reports (other academic/artistic)abstract
- In this article, the results concerning hypothesis testing in multivariate normal models with block circular covariance structures are obtained. Hypotheses about a general block structure of the covariance matrix and specific covariance parameters have been of main interest. In addition, the tests about patterned mean vectors have been considered.The corresponding likelihood ratio statistics are derived and their null distributions are studied.
|
|
21. |
|
|
22. |
|
|
23. |
- Von Rosen, Dietrich, et al.
(author)
-
Explicit estimators in unbalanced mixed linear models.
- 2015
-
In: Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday. - Växjö : Linnaeus University Press, Växjö, Sweden. - 9789187925900 ; , s. 121-125
-
Book chapter (other academic/artistic)
|
|
24. |
- von Rosen, Tatjana, et al.
(author)
-
A new method for obtaining explicit estimators in unbalanced mixed linear models
- 2020
-
In: Statistical papers. - : Springer Science and Business Media LLC. - 0932-5026 .- 1613-9798. ; 61:1, s. 371-383
-
Journal article (peer-reviewed)abstract
- The general unbalanced mixed linear model with two variance components is considered. Through resampling it is demonstrated how the fixed effects can be estimated explicitly. It is shown that the obtained nonlinear estimator is unbiased and its variance is also derived. A condition is given when the proposed estimator is recommended instead of the ordinary least squares estimator.
|
|
25. |
|
|
26. |
- von Rosen, Tatjana, et al.
(author)
-
Bilinear regression with random effects and reduced rank restrictions
- 2020
-
In: Japanese journal of statistics and data science. - : Springer Science and Business Media LLC. - 2520-8756 .- 2520-8764. ; 3:1, s. 63-72
-
Journal article (peer-reviewed)abstract
- Bilinear models with three types of effects are considered: fixed effects, random effects and latent variable effects. In the literature, bilinear models with random effects and bilinear models with latent variables have been discussed but there are no results available when combining random effects and latent variables. It is shown, via appropriate vector space decompositions, how to remove the random effects so that a well-known model comprising only fixed effects and latent variables is obtained. The spaces are chosen so that the likelihood function can be factored in a convenient and interpretable way. To obtain explicit estimators, an important standardization constraint on the random effects is assumed to hold. A theorem is presented where a complete solution to the estimation problem is given.
|
|
27. |
- von Rosen, Tatjana, et al.
(author)
-
Bilinear regression with rank restrictions on the mean and the dispersion matrix
- 2018
-
Reports (other academic/artistic)abstract
- A bilinear regression model with rank restrictions imposed on the mean-parameter matrix and on the dispersion matrix is studied. Maximum likelihood inspired estimates are derived. The approach generalizes classical reduced rank regression analysis and principal component analysis. It is shown via a simulation study and a real example that even for small dimensions the method works as well as reduced rank regression analysis whereas the approach in this article also can be used when the dimension is large.
|
|
28. |
- von Rosen, Tatjana, et al.
(author)
-
Explicit estimators in unbalanced mixed linear models
- 2015
-
In: Festschrift in honor of professor Ghazi Shukur on the occasion of his 60th birthday. - Växjö : Linnaeus University Press. - 9789187925900 ; , s. 121-125
-
Book chapter (other academic/artistic)abstract
- The general unbalanced mixed linear model is considered. Throughresampling it is shown how the fixed effects can explicitly be estimated.The obtained estimator is non-linear but unbiased.
|
|
29. |
|
|
30. |
- von Rosen, Tatjana, et al.
(author)
-
On Estimation in Some Reduced Rank Extended Growth Curve Models
- 2017
-
In: Mathematical Methods of Statistics. - New York, NY, United States : Allerton Press, Inc.. - 1066-5307 .- 1934-8045. ; 26:4, s. 299-310
-
Journal article (peer-reviewed)abstract
- The general multivariate analysis of variance model has been extensively studied in the statistical literature and successfully applied in many different fields for analyzing longitudinal data. In this article, we consider the extension of this model having two sets of regressors constituting a growth curve portion and a multivariate analysis of variance portion, respectively. Nowadays, the data collected in empirical studies have relatively complex structures though often demanding a parsimonious modeling. This can be achieved for example through imposing rank constraints on the regression coefficient matrices. The reduced rank regression structure also provides a theoretical interpretation in terms of latent variables. We derive likelihood based estimators for the mean parameters and covariance matrix in this type of models. A numerical example is provided to illustrate the obtained results.
|
|
31. |
- von Rosen, Tatjana, et al.
(author)
-
Small area estimation using reduced rank regression models
- 2020
-
In: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 49:13, s. 3286-3297
-
Journal article (peer-reviewed)abstract
- Small area estimation techniques have got a lot of attention during the last decades due to their important applications in survey studies. Mixed linear models and reduced rank regression analysis are jointly used when considering small area estimation. Estimates of parameters are presented as well as prediction of random effects and unobserved area measurements.
|
|
32. |
|
|
33. |
- Wahlund, Björn, et al.
(author)
-
EEG data, fractal dimension and multivariate statistics
- 2010
-
In: Journal of Computer Science and Engineering. - 2043-9091. ; 3:1, s. 10-16
-
Journal article (peer-reviewed)abstract
- The objective of this paper is to discuss the concept of Inverse Problem, i.e. how to obtain information via data about a complex mathematical model. We propose that by merging ideas from applied mathematics with ideas from multivariate statistical inference it is possible to find solutions or good approximation of many complex scientific problems.
|
|
34. |
- Eckersten, Henrik, et al.
(author)
-
Framtida risker och hot mot svensk spannmåls- respektive mjölkproduktion : en analys av forskningsbehov för att bedöma risker
- 2015
-
Reports (other academic/artistic)abstract
- Vad är syftet med denna Riskanalys? Svensk spannmåls- och mjölkproduktion beror på många faktorer av vilka flera är så kallade biofysiska, dvs i allt väsentligt är de av naturvetenskaplig karaktär (t ex väder, sjukdomar mm). En del förändringar i dessa förutsättningar utgör hot. Vår studie avser att identifiera några av dessa hot och utvärdera, utifrån vetenskapligt testade metodiker, sannolikheten för att de orsakar en skada på produktionen. Detta kräver dock ett mycket omfattande arbete och i denna studie har vi därför begränsat oss till att (i) strukturera hur en vetenskapligt baserad riskanalys bör gå till, och (ii) göra ett antal preliminära riskanalyser för att (iii) identifiera kunskapsluckor som behöver forskas på för att analysen ska kunna antas vila på en vetenskaplig grund. Vad menar vi med Risk? Vi har definierat risk som sannolikheten att ett hot orsakar en viss negativ konsekvens för den skyddsvärda tillgången. Av dessa termer är kanske den sistnämnda den mest centrala. Vad är det vi vill skydda? Vi har valt ut två tillgångar, Sveriges nationella spannmåls- respektive mjölkproduktion och avser då den produktion som lämnar gården, eller används inom gården, och att de skyddas så att de förblir ungefär av den omfattningen de har i dagsläget. Hoten mot denna produktion har valts utifrån förslag från tidigare studier, workshop, tillgången på experter och att hoten ska vara av biofysisk karaktär. Vilket hot som verkligen utgör en stor risk vet vi ju dock inte förrän efter riskanalysen är utförd och valen av hot bygger därför på en preliminär uppskattning. Biofysisk karaktär innebär att vi främst analyserat naturvetenskapliga hot. Hoten orsakar effekter på produktionen i mätbara termer som sedan översätts till en mer abstrakt skala från ingen till extremt negativ konsekvens. Beroende på olika osäkerhetsfaktorer erhåller vi flera konsekvensvärden för ett givet hot, och fördelningen av dessa på konsekvensskalan utgör ett mått på sannolikheten. Risken anges alltså som ett förhållande mellan konsekvens och sannolikhet. Varför har vi gjort denna systemavgränsning? Riskanalysen har två huvudaktörer; riskhanteraren som definierar vad som ska anlyseras och analysfunktionen som utför analysen. Riskhanteraren är i vårt fall styrgruppen för SLUs forskningsprogram Framtidens lantbruk (FA, 2015) som har definierat typen av hot och de skyddsvärda tillgångarna som ska analyseras. Vi som utfört denna studie är analysfunktionen, och har alltså dessa definitioner som en utgångspunkt. Om vi ändå tillåter oss att spekulera kring valet av spannmåls- respektive mjölkproduktionen så kan det motiveras av SLU's nationella ansvar vad avser den vetenskapliga kompetensen inom de areella näringarna. Ett fokus på biofysiska hot motiveras av att dessa är potentiellt stora och växande, såsom t ex är fallet vad avser klimatförändringar. Riskanalyser av denna typ bildar centrala underlag för att formulera olika strategier, t ex angående livsmedelsförsörjning. Hur har arbetet gått till? Riskanalyserna har utförts för ett antal "krisscenarier"; fyra avseende hot mot spannmålsproduktionen (Radioaktivt-nedfall, Virus-i-spannmål, Herbicidresistens och Extremt-sommarväder) och tre avseende mjölkproduktionen (Leptospiros-utbrott, Foderimport-stopp och Värmebölja). Analysen tar sin utgångspunkt i ett omvärldsscenario som definierar de yttre förutsättningarna för vad som antas inträffa. Detta ligger till grund för att identifiera troliga hot mot produktionen och vilka åtgärder som förväntas vidtas. Vi har sedan utgått från att dessa hot och åtgärder verkligen har hänt när vi mha våra förklaringsmodeller bestämt effekterna på produktionen i termer av mätbara enheter ("metrics"; t ex procentuell minskning av lokal eller regional veteproduktion). Dessa effekter tolkas/integreras sedan till en konsekvens för, helst den nationella, men i realiteten främst den regionala produktionen i fem nivåer (ingen, liten, måttlig, stor respektive extrem). Osäkerheter i bedömningarna innebär att flera alternativa konsekvenser erhålls, för ett givet hot, och som ligger till grund för en sannolikhetsbedömning. Analyserna har gjorts av experter inom respektive hots vetenskapliga område, men som haft begränsade förutsättningar (av tidsskäl) att göra tillräckligt många bedömningar för att erhålla ett tillförlitligt mått på sannolikhetsfördelningen (osäkerheten). Istället har vi, vilket också är ett huvudsyfte med studien, huvudsakligen försökt identifiera de kunskapsluckor i förklaringsmodellerna som begränsat våra möjligheter att kunna göra vetenskapligt baserade bedömningar av effekterna (se vidare Appendix 3). Vad är resultatet? Vi har gjort vissa grova skattningar av sannolikheten trots det bristfälliga antalet bedömningar av konsekvenser. Om ett radioaktivt nedfall sker i en region får det extrema konsekvenser för dess spannmålsproduktion på regional nivå. Ett omfattande angrepp av jordburna virus orsakar en måttlig eller stor konsekvens. En utvecklad herbicidresistens hos ogräsen orsakar i huvudsak en liten till måttlig konsekvens. En extremt torr sommar kan ett år orsaka en stor konsekvens och ett annat år ingen alls. Likaledes orsakar en Regnig-sensommar i ca hälften av fallen ingen konsekvens, men för de resterande åren kan alla grader av konsekvenser uppstå på spannmålsproduktionen. För mjölkproduktionen orsakar samtliga tre hot (Leptospiros-utbrott, Foderimport-stopp och Värmebölja) en liten till måttlig konsekvens. Vad avser ett importsopp för foder är detta under förutsättning att olika åtgärdsprogram kombineras. Om fokus läggs på endast ett åtgärdsprogram ökar risken väsentligt. Dessa skattningar ska alltså inte betraktas som en vetenskapligt baserad analys i nuläget, utan demonstrerar främst exempel på resultat från sådana analyser. Skattningarna har hjälpt oss att identifiera vilka kunskaper vi saknar för att analyserna ska kunna betraktas som vetenskapligt baserade (se vidare Tabell 4.3a; sammanfattningar av respektive scenario finns i Resultatdelen). Analyserna har ibland också lett till att vi identifierat följdhändelser som faller utanför systemavgränsningen för vår studie och som andra studier har till uppgift att utreda. Många av de hot vi analyserat kan leda till betydande ekonomiska konsekvenser för enskilda företag, vilket i sin tur utgör hot mot produktionen. För denna analys krävs dock socioekonomiska analyser. Vi ser här också kopplingar mellan krisscenarier som är av biofysisk karaktär, t ex kan foder kontaminerat med radioaktivt cesium utgöra ett hot mot mjölkproduktionen. Vår studie har dock bara analyserat ett krisscenarios inverkan på antigen spannmåls- eller mjölkproduktionen.Vilka är de viktigaste slutsatserna? En central fråga är: Hur trovärdiga/säkra är dessa förutsägelser? Risk avser en förutsägelse om något som ännu inte hänt. Det första som behövs är alltså någon form av modell. Dessa modeller kan vara av olika sort i termer av vilken empirisk kunskap de använder för extrapolering (t ex funktioner, behandlingseffekter, mm), om de är objektiva och om de är transparenta. Alla modeller är osäkra i någon mening. Dock saknas i alla de fall vi undersökt mått på modellernas förutsägelseförmåga (med något enstaka undantag). En allmän slutsats blir att forskningen behöver inriktas mot att testa modellernas förutsägelseförmåga mot observationer för att kunna bidra till en vetenskapligt baserad riskanalys av spannmåls- respektive mjölkproduktionen. Detta innebär att experiment- och försöksupplägg behöver göras utifrån hypoteser (modeller) om hur de dynamiska förloppen beror på varierande förutsättningar och omgivningsförhållanden. T ex behöver de statistiska relationerna för hur Extremt-sommarväder påverkar spannmålsproduktionen, som används i vår studie, kompletteras med tester av grödmodeller som kan beakta flera vädervariablers samtida variationer i både tid och rum. För kunskapsluckor som är specifika för respektive hot, se Tabell 4.4Sammanfattningsvis behövs (i) fler förutsägelser av respektive potentiellt hots konsekvenser på produktionen, med modeller som har någon form av graderad tillförlitlighet, för att erhålla mått på osäkerheter. Dessutom behövs det (ii) tester av hypoteser för uppskalningar från kontrollerade experiment och försök (på en liten skala i tid och rum) till regional och nationell skala över flera år, och (iii) utveckling av metodiker för hur sannolikheter för hot, åtgärder respektive konsekvenser kan kombineras till en sannolikhetsfördelning som inbegriper bedömningsosäkerheter för alla dessa faktorer. Troligtvis behövs också att fler potentiella biofysiska hot analyseras. Hur går vi vidare? En mer fullständig riskanalys som inkluderar alla potentiellt stora hot mot produktionen, och samtidigt är vetenskapligt baserad, kräver att potentiella hot utreds kontinuerligt inom respektive produktionsrelaterat ämnesområde vid SLU. Detta kräver troligen att verksamheter som testar hypoteser för att förutsäga effekter av hot knyts nära den experimentella forskningen och experter inom respektive ämnesområde. Det krävs troligen också att en syntesverksamhet etableras på en ämnesövergripande nivå där metodiker kan standardardiseras, och olika hot och dess konsekvenser kan jämföras och kombineras. En sådan fungerande verksamhet behöver utvidga systemgränserna jämfört med vår studie, genom att sannolikheter för att hot uppkommer och att åtgärder faktiskt vidtas, också bedöms. Dessa sannolikheter behöver sedan integreras med sannolikheterna för konsekvenserna på produktionen. Därefter kan riskanalysen utökas till att inbegripa en mer a
|
|
35. |
- Ahmad, M. Rauf, et al.
(author)
-
A note on mean testing for high dimensional multivariate data under non-normality
- 2013
-
In: Statistica Neerlandica. - : Wiley. - 0039-0402 .- 1467-9574. ; 67:1, s. 81-99
-
Journal article (peer-reviewed)abstract
- A test statistic is considered for testing a hypothesis for the mean vector for multivariate data, when the dimension of the vector, p, may exceed the number of vectors, n, and the underlying distribution need not necessarily be normal. With n,p?8, and under mild assumptions, but without assuming any relationship between n and p, the statistic is shown to asymptotically follow a chi-square distribution. A by product of the paper is the approximate distribution of a quadratic form, based on the reformulation of the well-known Box's approximation, under high-dimensional set up. Using a classical limit theorem, the approximation is further extended to an asymptotic normal limit under the same high dimensional set up. The simulation results, generated under different parameter settings, are used to show the accuracy of the approximation for moderate n and large p.
|
|
36. |
- Ahmad, M. Rauf, et al.
(author)
-
A U-statistics Based Approach to Mean Testing for High Dimensional Multivariate Data Under Non-normality
- 2011
-
Reports (other academic/artistic)abstract
- A test statistic is considered for testing a hypothesis for the mean vector for multivariate data, when the dimension of the vector, p, may exceed the number of vectors, n, and the underlying distribution need not necessarily be normal. With n, p large, and under mild assumptions, the statistic is shown to asymptotically follow a normal distribution. A by product of the paper is the approximate distribution of a quadratic form, based on the reformulation of well-known Box's approximation, under high-dimensional set up.
|
|
37. |
- Ahmad, M. Rauf, et al.
(author)
-
Some Tests of Covariance Matrices for High Dimensional Multivariate Data
- 2011
-
Reports (other academic/artistic)abstract
- Test statistics for sphericity and identity of the covariance matrix are presented, when the data are multivariate normal and the dimension, p, can exceed the sample size, n. Using the asymptotic theory of U-statistics, the test statistics are shown to follow an approximate normal distribution for large p, also when p >> n. The statistics are derived under very general conditions, particularly avoiding any strict assumptions on the traces of the unknown covariance matrix. Neither any relationship between n and p is assumed. The accuracy of the statistics is shown through simulation results, particularly emphasizing the case when p can be much larger than n. The validity of the commonly used assumptions for high-dimensional set up is also briefly discussed.
|
|
38. |
- Ahmad, M. Rauf, et al.
(author)
-
Tests for high-dimensional covariance matrices using the theory of U-statistics
- 2015
-
In: Journal of Statistical Computation and Simulation. - : Informa UK Limited. - 0094-9655 .- 1563-5163. ; 85:13, s. 2619-2631
-
Journal article (peer-reviewed)abstract
- Test statistics for sphericity and identity of the covariance matrix are presented, when the data are multivariate normal and the dimension, p, can exceed the sample size, n. Under certain mild conditions mainly on the traces of the unknown covariance matrix, and using the asymptotic theory of U-statistics, the test statistics are shown to follow an approximate normal distribution for large p, also when p >> n. The accuracy of the statistics is shown through simulation results, particularly emphasizing the case when p can be much larger than n. A real data set is used to illustrate the application of the proposed test statistics.
|
|
39. |
- Ahmad, M. Rauf, et al.
(author)
-
Tests of Covariance Matrices for High Dimensional Multivariate Data Under Non Normality
- 2015
-
In: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 44:7, s. 1387-1398
-
Journal article (peer-reviewed)abstract
- Ahmad et al. (in press) presented test statistics for sphericity and identity of the covariance matrix of a multivariate normal distribution when the dimension, p, exceeds the sample size, n. In this note, we show that their statistics are robust to normality assumption, when normality is replaced with certain mild assumptions on the traces of the covariance matrix. Under such assumptions, the test statistics are shown to follow the same asymptotic normal distribution as under normality for large p, also whenp >> n. The asymptotic normality is proved using the theory of U-statistics, and is based on very general conditions, particularly avoiding any relationship between n and p.
|
|
40. |
|
|
41. |
|
|
42. |
- Amiri, Saeid, et al.
(author)
-
A statistical study of similarities and dissimilarities in results between districts used in Swedish crop variety trials
- 2009
-
Reports (other academic/artistic)abstract
- The annual results of Swedish crop variety trials are presented in reports and on the internet for Sweden divided into seven regions (production areas) A-G covering southern Sweden. The yield results for test varieties are usually presented as ratios relative to the yield of a control variety. These ratios are presented per region, with the implicit assumption that differences in ratios may exist between regions. In this report, the division of agricultural districts into regions was investigated through cluster analyses. Districts that produced similar levels of yield or similar ratios were clustered into groups of similar districts. Cluster analyses were performed on regions, districts and soil types for spring barley, winter wheat and oats, based on a large data set of results from variety trials performed during the period 1997-2006. The study revealed that some regions, districts and soil types produce similar levels of yield or similar yield ratios. However, clusters of regions, districts or soil types that produce similar levels of yield do not always produce similar yield ratios
|
|
43. |
|
|
44. |
- Amiri, Saeid, et al.
(author)
-
On the efficiency of bootstrap method into the analysis contingency table
- 2011
-
In: Computer Methods and Programs in Biomedicine. - : Elsevier BV. - 0169-2607 .- 1872-7565. ; 104:2, s. 182-187
-
Journal article (peer-reviewed)abstract
- The bootstrap method is a computer intensive statistical method that is widely used in performing nonparametric inference. Categorica ldata analysis,inparticular the analysis of contingency tables, is commonly used in applied field. This work considers nonparametric bootstrap tests for the analysis of contingency tables. There are only a few research papers which exploit this field. The p-values of tests in contingency tables are discrete and should be uniformly distributed under the null hypothesis. The results of this article show that corresponding bootstrap versions work better than the standard tests. Properties of the proposed tests are illustrated and discussed using Monte Carlo simulations. This article concludes with an analytical example that examines the performance of the proposed tests and the confidence interval of the association coefficient.
|
|
45. |
- Amiri, Saeid, et al.
(author)
-
The SVM Approach for Box–Jenkins Models
- 2009
-
In: REVSTAT-Statistical Journal. - 1645-6726. ; 7:1, s. 23-36
-
Journal article (peer-reviewed)abstract
- Support Vector Machine (SVM) is known in classification and regression modeling. It has been receiving attention in the application of nonlinear functions. The aim is to motivate the use of the SVM approach to analyze the time series models. This is an effort to assess the performance of SVM in comparison with ARMA model. The applicability of this approach for a unit root situation is also considered.
|
|
46. |
|
|
47. |
|
|
48. |
|
|
49. |
- Byukusenge, Béatrice, et al.
(author)
-
On an Important Residual in the GMANOVA-MANOVA Model
- 2022
-
In: Journal of Statistical Theory and Practice. - : SPRINGER. - 1559-8608 .- 1559-8616. ; 16:2
-
Journal article (peer-reviewed)abstract
- The main goal of this paper is to study residuals in a special case of the extended growth curve model, called the GMANOVA-MANOVA model. With the help of an example, emphasis is put on the model formulation, interpretation of the model and residuals that vanish, with a discussion about the reasons behind this fact and the consequence of it.
|
|
50. |
- Byukusenge, Béatrice, 1984-, et al.
(author)
-
On Residual Analysis in the GMANOVA-MANOVA Model
- 2023
-
In: Trends in Mathematical, Information and Data Sciences: A Tribute to Leandro Pardo. - Cham : Springer International Publishing. - 9783031041365 - 9783031041372 ; , s. 287-305
-
Book chapter (peer-reviewed)abstract
- In this article, the GMANOVA-MANOVA model is considered. Two different matrix residuals are established. The interpretation of the residuals is discussed and several properties are verified. A data set illustrates how the residuals can be used.
|
|