| 1. |
- Alam, Md Moudud, 1976-
(författare)
-
Likelihood Prediction for Generalized Linear Mixed Models under Covariate Uncertainty
- 2014
-
Ingår i: Communications in Statistics - Theory and Methods. - : Informa UK Limited. - 0361-0926 .- 1532-415X. ; 43:2, s. 219-234
-
Tidskriftsartikel (refereegranskat)abstract
- This article presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction are explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. This article outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson errors-in-variable generalized linear model, it has been shown in certain cases that LP produces better results than already known methods.
|
|
| 2. |
- Jia, Tao, 1983-, et al.
(författare)
-
An empirical study on human mobility and its agent-based modeling
- 2012
-
Ingår i: Journal of Statistical Mechanics. - Bristol : Institute of Physics Publishing (IOPP). - 1742-5468 .- 1742-5468.
-
Tidskriftsartikel (refereegranskat)abstract
- This paper aims to analyze the GPS traces of 258 volunteers for a better understanding of both the human mobility patterns and the mechanism. We report the regular and scaling properties of human mobility from several aspects, and importantly we find its levy flight characteristic which is consistent with the previous studies. We further assume two factors that may govern the levy flight property: (1) the scaling and hierarchical properties of the purpose clusters which serve as the underlying spatial structure, and (2) the individual preferential behavior. To verify the assumptions, we implement an agent-based model with the two factors, and the simulated agents indeed reproduce the same levy flight pattern as the observed one. In order to enable the model to reproduce more mobility patterns, we add the model a third factor, the jumping factor which means the probability that one person may cancel the regular mobility schedule and visit a random place. With this factor, our model could cover a relatively wide range of human mobility patterns with exponent values from 1.55 to 2.05.
|
|
| 3. |
- Li, Dao
(författare)
-
Common features in vector nonlinear time series models
- 2013
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in thesearea.Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified.The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An F-type test for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail, and thereafter illustrated within two corresponding macroeconomic data sets.
|
|
| 4. |
- Carling, Kenneth, et al.
(författare)
-
Confidence in heuristic solutions?
- 2015
-
Ingår i: Journal of Global Optimization. - : Springer Science and Business Media LLC. - 0925-5001 .- 1573-2916. ; 63:2, s. 381-399
-
Tidskriftsartikel (refereegranskat)abstract
- Solutions to combinatorial optimization problems frequently rely on heuristics to minimize an objective function. The optimum is sought iteratively and pre-setting the number of iterations dominates in operations research applications, which implies that the quality of the solution cannot be ascertained. Deterministic bounds offer a mean of ascertaining the quality, but such bounds are available for only a limited number of heuristics and the length of the interval may be difficult to control in an application. A small, almost dormant, branch of the literature suggests using statistical principles to derive statistical bounds for the optimum. We discuss alternative approaches to derive statistical bounds. We also assess their performance by testing them on 40 test p-median problems on facility location, taken from Beasley’s OR-library, for which the optimum is known. We consider three popular heuristics for solving such location problems; simulated annealing, vertex substitution, and Lagrangian relaxation where only the last offers deterministic bounds. Moreover, we illustrate statistical bounds in the location of 71 regional delivery points of the Swedish Post. We find statistical bounds reliable and much more efficient than deterministic bounds provided that the heuristic solutions are sampled close to the optimum. Statistical bounds are also found computationally affordable.
|
|
| 5. |
- Mischenko, Kateryna, et al.
(författare)
-
Assessing a multiple QTL search using the variance component model
- 2010
-
Ingår i: Computational biology and chemistry (Print). - : Elseiver. - 1476-9271 .- 1476-928X. ; 34:1, s. 34-41
-
Tidskriftsartikel (refereegranskat)abstract
- Development of variance component algorithms in genetics has previously mainly focused on animal breeding models or problems in human genetics with a simple data structure. We study alternative methods for constrained likelihood maximization in quantitative trait loci (QTL) analysis for large complex pedigrees. We apply a forward selection scheme to include several QTL and interaction effects, as well as polygenic effects, with up to five variance components in the model. We show that the implemented active set and primal-dual schemes result in accurate solutions and that they are robust. In terms of computational speed, a comparison of two approaches for approximating the Hessian of the log-likelihood shows that the method using an average information matrix is the method of choice for the five-dimensional problem. The active set method, with the average information method for Hessian computation, exhibits the fastest convergence with an average of 20 iterations per tested position, where the change in variance components <0.0001 was used as convergence criterion.
|
|
| 6. |
- Aghanavesi, Somayeh, 1981-, et al.
(författare)
-
Verification of a Method for Measuring Parkinson's Disease Related Temporal Irregularity in Spiral Drawings
- 2017
-
Ingår i: Sensors. - Basel : MDPI AG. - 1424-8220. ; 17:10
-
Tidskriftsartikel (refereegranskat)abstract
- -value = 0.02). Test-retest reliability of TIS was good with Intra-class Correlation Coefficient of 0.81. When assessing changes in relation to treatment, TIS contained some information to capture changes from Off to On and wearing off effects. However, the correlations between TIS and clinical scores (UPDRS and Dyskinesia) were weak. TIS was able to differentiate spiral drawings drawn by patients in an advanced stage from those drawn by healthy subjects, and TIS had good test-retest reliability. TIS was somewhat responsive to single-dose levodopa treatment. Since TIS is an upper limb high-frequency-based measure, it cannot be detected during clinical assessment.
|
|
| 7. |
- Alam, Moudud
(författare)
-
An efficient algorithm for the pseudo likelihood estimation of the generalized linear mixed models (GLMM) with correlated random effects
- 2009
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with correlated random effects. The proposed estimation technique does not require reparametarisation of the model. Multivariate Taylor's approximation has been used to approximate the intractable integrals in the likelihood function of the GLMM. Based on the analytical expression for the estimator of the covariance matrix of the random effects, a condition has been presented as to when such a covariance matrix can be estimated through the estimates of the random effects. An application of the model with a binary response variable has been presented using a real data set on credit defaults from two Swedish banks. Due to the use of two-step estimation technique, proposed algorithm outperforms the conventional pseudo likelihood algorithms in terms of computational time.
|
|
| 8. |
- Alam, Moudud, 1976-, et al.
(författare)
-
Fitting conditional and simultaneous autoregressive spatial models in hglm
- 2015
-
Ingår i: The R Journal. - 2073-4859. ; 7:2, s. 5-18
-
Tidskriftsartikel (refereegranskat)abstract
- We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.
|
|
| 9. |
- Alam, Moudud, et al.
(författare)
-
Fitting spatial models in the R package: hglm
- 2014
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).
|
|
| 10. |
|
|
