| 1. |
- Asar, O., et al.
(författare)
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Linear mixed effects models for non-Gaussian continuous repeated measurement data
- 2020
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Ingår i: Journal of the Royal Statistical Society Series C-Applied Statistics. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 69:5, s. 1015-1065
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Tidskriftsartikel (refereegranskat)abstract
- We consider the analysis of continuous repeated measurement outcomes that are collected longitudinally. A standard framework for analysing data of this kind is a linear Gaussian mixed effects model within which the outcome variable can be decomposed into fixed effects, time invariant and time-varying random effects, and measurement noise. We develop methodology that, for the first time, allows any combination of these stochastic components to be non-Gaussian, using multivariate normal variance-mean mixtures. To meet the computational challenges that are presented by large data sets, i.e. in the current context, data sets with many subjects and/or many repeated measurements per subject, we propose a novel implementation of maximum likelihood estimation using a computationally efficient subsampling-based stochastic gradient algorithm. We obtain standard error estimates by inverting the observed Fisher information matrix and obtain the predictive distributions for the random effects in both filtering (conditioning on past and current data) and smoothing (conditioning on all data) contexts. To implement these procedures, we introduce an R package: ngme. We reanalyse two data sets, from cystic fibrosis and nephrology research, that were previously analysed by using Gaussian linear mixed effects models.
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| 2. |
- Bobkova, Evgeniya, 1988, et al.
(författare)
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Structure of Plot Systems and Economic Activity in Cities: Linking Plot Types to Retail and Food Services in London, Amsterdam and Stockholm
- 2019
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Ingår i: Urban Science. - : MDPI AG. - 2413-8851. ; 3:3
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Tidskriftsartikel (refereegranskat)abstract
- Plot systems (also referred to as "property", "parcel", or "lot") are generally recognised as the organisational framework of urban form that contributes to the economic performance of cities. However, studies that link the spatial form of plots to economic data are limited. The paper builds on the theory of Webster and Lai, which argues that the process of urbanisation is aligned with increased subdivision of property rights (increased division of land into plots, for example) due to the process of economic specialisation that is typical of cities. The aim of the paper is to test this theory by analysing whether there is a correlation between: (a) the shape and structure of plot systems, which are classified as types based on three plot metrics (size, compactness, and frontage index) and b) economic activity, measured as the concentration of retail and food activities per plot. The paper will use statistical analysis to relate plot types to economic activity in three European cities (London, Amsterdam, and Stockholm). The results provide empirical support for our initial hypothesis and Webster and Lai’s theory, which states that plots of smaller size, more regular shape, and smaller frontage generally correspond to a higher concentration of economic activity in cities.
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| 3. |
- Bolin, David, 1983, et al.
(författare)
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Calculating Probabilistic Excursion Sets and Related Quantities Using excursions
- 2018
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Ingår i: Journal of Statistical Software. - : Foundation for Open Access Statistic. - 1548-7660. ; 86:5, s. 1-20
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Tidskriftsartikel (refereegranskat)abstract
- The R software package excursions contains methods for calculating probabilistic excursion sets, contour credible regions, and simultaneous confidence bands for latent Gaussian stochastic processes and fields. It also contains methods for uncertainty quantification of contour maps and computation of Gaussian integrals. This article describes the theoretical and computational methods used in the package. The main functions of the package are introduced and two examples illustrate how the package can be used.
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| 4. |
- Bolin, David, 1983, et al.
(författare)
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Calibrating regionally downscaled precipitation over Norway through quantile-based approaches
- 2016
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Ingår i: Advances in Statistical Climatology, Meteorology and Oceanography. - 2364-3579 .- 2364-3587. ; 2, s. 39-47
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Tidskriftsartikel (refereegranskat)abstract
- Dynamical downscaling of earth system models is intended to produce high-resolution climate in- formation at regional to local scales. Current models, while adequate for describing temperature distributions at relatively small scales, struggle when it comes to describing precipitation distributions. In order to better match the distribution of observed precipitation over Norway, we consider approaches to statistical adjustment of the output from a regional climate model when forced with ERA-40 reanalysis boundary conditions. As a second step, we try to correct downscalings of historical climate model runs using these transformations built from downscaled ERA-40 data. Unless such calibrations are successful, it is difficult to argue that scenario-based downscaled climate projections are realistic and useful for decision makers. We study both full quantile cali- brations and several different methods that correct individual quantiles separately using random field models. Results based on cross-validation show that while a full quantile calibration is not very effective in this case, one can correct individual quantiles satisfactorily if the spatial structure in the data are accounted for. Interestingly, different methods are favoured depending on whether ERA-40 data or historical climate model runs are adjusted.
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| 5. |
- Bolin, David, 1983, et al.
(författare)
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Excursion and contour uncertainty regions for latent Gaussian models
- 2015
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Ingår i: Journal of The Royal Statistical Society Series B-statistical Methodology. - : Oxford University Press (OUP). - 1369-7412 .- 1467-9868. ; 77:1, s. 85-106
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Tidskriftsartikel (refereegranskat)abstract
- In several areas of application ranging from brain imaging to astrophysics and geostatistics, an important statistical problem is to find regions where the process studied exceeds a certain level. Estimating such regions so that the probability for exceeding the level in the entire set is equal to some predefined value is a difficult problem connected to the problem of multiple significance testing. In this work, a method for solving this problem, as well as the related problem of finding credible regions for contour curves, for latent Gaussian models is proposed. The method is based on using a parametric family for the excursion sets in combination with a sequential importance sampling method for estimating joint probabilities. The accuracy of the method is investigated by using simulated data and an environmental application is presented.
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| 6. |
- Bolin, David, 1983, et al.
(författare)
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Fast estimation of spatially dependent temporal vegetation trends using Gaussian Markov random fields
- 2009
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Ingår i: Computational Statistics and Data Analysis. - : Elsevier BV. - 0167-9473. ; 53:8, s. 2885-2896
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Tidskriftsartikel (refereegranskat)abstract
- There is a need for efficient methods for estimating trends in spatio-temporal Earth Observation data. A suitable model for such data is a space-varying regression model, where the regression coefficients for the spatial locations are dependent. A second order intrinsic Gaussian Markov Random Field prior is used to specify the spatial covariance structure. Model parameters are estimated using the Expectation Maximisation (EM) algorithm, which allows for feasible computation times for relatively large data sets. Results are illustrated with simulated data sets and real vegetation data from the Sahel area in northern Africa. The results indicate a substantial gain in accuracy compared with methods based on independent ordinary least squares regressions for the individual pixels in the data set. Use of the EM algorithm also gives a substantial performance gain over Markov Chain Monte Carlo-based estimation approaches. © 2008 Elsevier B.V. All rights reserved.
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| 7. |
- Bolin, David, 1983, et al.
(författare)
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Functional ANOVA modelling of pedestrian counts on streets in three European cities
- 2021
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Ingår i: Journal of the Royal Statistical Society. Series A, (Statistics in Society). - : Oxford University Press (OUP). - 1467-985X .- 0964-1998. ; 184:4, s. 1176-1198
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Tidskriftsartikel (refereegranskat)abstract
- The relation between pedestrian flows, the structure of the city and the street network is of central interest in urban research. However, studies of this have traditionally been based on small data sets and simplistic statistical methods. Because of a recent large-scale cross-country pedestrian survey, there is now enough data available to study this in greater detail than before, using modern statistical methods. We propose a functional ANOVA model to explain how the pedestrian flow for a street varies over the day based on its density type, describing the nearby buildings, and street type, describing its role in the city’s overall street network. The model is formulated and estimated in a Bayesian framework using hour-by-hour pedestrian counts from the three European cities, Amsterdam, London and Stockholm. To assess the predictive power of the model, which could be of interest when building new neighbourhoods, it is compared with four common methods from machine learning, including neural networks and random forests. The results indicate that this model works well but that there is room for improvement in capturing the variability in the data, especially between cities.
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| 8. |
- Bolin, David, 1983, et al.
(författare)
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Latent Gaussian random field mixture models
- 2019
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Ingår i: Computational Statistics & Data Analysis. - : Elsevier BV. - 0167-9473. ; 130, s. 80-93
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Tidskriftsartikel (refereegranskat)abstract
- For many problems in geostatistics, land cover classification, and brain imaging the classical Gaussian process models are unsuitable due to sudden, discontinuous, changes in the data. To handle data of this type, we introduce a new model class that combines discrete Markov random fields (MRFs) with Gaussian Markov random fields. The model is defined as a mixture of several, possibly multivariate, Gaussian Markov random fields. For each spatial location, the discrete MRF determines which of the Gaussian fields in the mixture that is observed. This allows for the desired discontinuous changes of the latent processes, and also gives a probabilistic representation of where the changes occur spatially. By combining stochastic gradient minimization with sparse matrix techniques we obtain computationally efficient methods for both likelihood-based parameter estimation and spatial interpolation. The model is compared to Gaussian models and standard MRF models using simulated data and in application to upscaling of soil permeability data. (C) 2018 Elsevier B.V. All rights reserved.
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| 9. |
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| 10. |
- Bolin, David, 1983, et al.
(författare)
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Multivariate type G Matern stochastic partial differential equation random fields
- 2020
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Ingår i: Journal of the Royal Statistical Society Series B-Statistical Methodology. - : Oxford University Press (OUP). - 1369-7412 .- 1467-9868.
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Tidskriftsartikel (refereegranskat)abstract
- For many applications with multivariate data, random-field models capturing departures from Gaussianity within realizations are appropriate. For this reason, we formulate a new class of multivariate non-Gaussian models based on systems of stochastic partial differential equations with additive type G noise whose marginal covariance functions are of Matern type. We consider four increasingly flexible constructions of the noise, where the first two are similar to existing copula-based models. In contrast with these, the last two constructions can model non-Gaussian spatial data without replicates. Computationally efficient methods for likelihood-based parameter estimation and probabilistic prediction are proposed, and the flexibility of the models suggested is illustrated by numerical examples and two statistical applications.
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