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Control for Omitted Variables in the Analysis of Panel and Other Longitudinal Data
2010
Geographical Analysis
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Davies and Robert Crouchley / 7
With exogenous variables, the model of equation (2) together with a beta mixing distribution for the outcome probability gives the stationary, zero-order, beta-logistic ...
confidence in any inference from longitudinal data unless the statistical methodology allows for variation due to omitted variables. ...
doi:10.1111/j.1538-4632.1985.tb00823.x
fatcat:2jmy2soybzezjmer6qc4y6e67i
A stochastic comparison study for the smallest and largest ordered statistic from Weibull-G and Gompertz Makeham distribution
[article]
2020
arXiv
pre-print
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In this paper, we have discussed the stochastic comparison of the smallest and largest ordered statistic from independent heterogeneous Weibull-G random variables and Gompertz Makeham random variables. ...
We compare systems arising from taking different model parameters and obtain stochastic ordering results under the condition of multivariate chain majorization. ...
In this paper we have discussed the stochastic comparison of the smallest and largest ordered statistic from independent heterogeneous Weibull-G random variables. ...
arXiv:2002.12474v1
fatcat:w46kabraincn7limdiawivrqje
Dispersal and ecological traits explain differences in beta diversity patterns of European beetles
2015
Journal of Biogeography
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Additionally, beta diversity patterns were characterized as a multivariate pairwise dissimilarity matrix among pairs of countries for each beetle clade. ...
Aim Disentangling the contributions of niche and dispersal processes as species distribution drivers is crucial from both theoretical and practical standpoints. ...
ACKNOWLEDGEMENTS We thank Paula Arribas, Kirsten Miller and three anonymous referees for comments to a previous version of this manuscript. ...
doi:10.1111/jbi.12523
fatcat:kzt4grmqdzaxng63htd5xgzj5m
Spatial community variability: Interactive effects of predators and isolation on stochastic community assembly
[article]
2020
bioRxiv
pre-print
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change the relative importance of stochastic and non-stochastic processes on community variability. ...
more abundant, irrespective of their order of colonization. ...
This method enables statistical tests of treatment effects on both mean observed beta-diversity and mean beta-deviation (see Vannette & Fukami 2017) . ...
doi:10.1101/2020.12.22.423949
fatcat:k2lfy72oevawhoon76eh34owda
Bernoulli Regression Models: Revisiting the Specification of Statistical Models with Binary Dependent Variables
2010
Journal of Choice Modeling
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The purpose of this paper is to re-examine the underlying probabilistic foundations of conditional statistical models with binary dependent variables using the PR approach. ...
The paper provides an explicit presentation of probabilistic model assumptions, guidance on model specification and estimation, and empirical application. ...
If ( ) j i Y f θ ; | X X is multivariate Bernoulli made up of K explanatory variables, then the index function would include an intercept, as well as first order , second order, and so on up to order K ...
doi:10.1016/s1755-5345(13)70033-2
fatcat:wgzqlgnvm5f2zpxtumf7suxnxy
Habitat heterogeneity drives the geographical distribution of beta diversity: the case of New Zealand stream invertebrates
2014
Ecology and Evolution
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This is one of the first studies accounting for stochastic effects while examining the ecological drivers of beta diversity. ...
We explored through a null model if beta diversity deviates from the expectation of stochastic assembly processes and whether the magnitude of the deviation varies geographically. ...
Acknowledgments We warmly acknowledge Jari Oksanen for advice on statistical analyses and use of the R program and Nathan Kraft for advice on null model analysis. ...
doi:10.1002/ece3.1124
pmid:25077020
pmcid:PMC4113293
fatcat:cbieskhmmzfaxjjjzl3i6zsf2u
Stochastic Newton Sampler: R Package sns
[article]
2015
arXiv
pre-print
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The R package sns implements Stochastic Newton Sampler (SNS), a Metropolis-Hastings Monte Carlo Markov Chain algorithm where the proposal density function is a multivariate Gaussian based on a local, second-order ...
When initial point is far from density peak, running SNS in non-stochastic mode by taking the Newton step, augmented with with line search, allows the MCMC chain to converge to high-density areas faster ...
from second-order Taylor series expansion of the log-density. ...
arXiv:1502.02008v1
fatcat:tphctnaz4fba7mvrjr562xbp6i
Bounds for mixtures of order statistics from exponentials and applications
2011
Journal of Multivariate Analysis
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Usual stochastic order Hazard rate order Mixture of distributions a b s t r a c t This paper deals with the stochastic comparison of order statistics and their mixtures. ...
For a random sample of size n from an exponential distribution with hazard rate λ, and for 1 ≤ k ≤ n, let us denote by F (λ) k:n the distribution function of the corresponding kth order statistic. ...
Acknowledgments I am very grateful to the three referees for the careful reading of the manuscript and for all important comments and suggestions which helped to considerably improve the presentation of ...
doi:10.1016/j.jmva.2011.01.006
fatcat:dcnfckbshbanbe23yss2mookwi
Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold
2021
Mathematics
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The results have significant implications for the implementation of smart beta strategies that rely heavily on the accuracy and stability of factor betas and yields. ...
We allow a separate threshold for each parameter; thus, the parameters may shift in an unsynchronized manner such that the model moves from one state to another when the change in the parameter exceeds ...
are usually large. ...
doi:10.3390/math9080915
fatcat:7bn5eu5oazhbpiqb3foudxhfti
Estimating Heterogeneous Customer Arrivals to a Large Retail store : A Bayesian Poisson model perspective
대형할인매점의 요일별 고객 방문 수 분석 및 예측 : 베이지언 포아송 모델 응용을 중심으로
2015
Korean Management Science Review
대형할인매점의 요일별 고객 방문 수 분석 및 예측 : 베이지언 포아송 모델 응용을 중심으로
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The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. ...
Still, the task of analyzing stochastic count data remains difficult and limited when it comes to multivariate count data, due to the interdependency between multiple time series. ...
All in all, the Bayesian multivariate analysis is beneficial for multivariate count data as it can clearly separate the common effects from individual effects, as well as taking advantages from the usual ...
doi:10.7737/kmsr.2015.32.2.069
fatcat:zcbe2u6xovd7tf45mgth56raim
A Note on Tractable State-Space Model for Symmetric Positive-Definite Matrices
2014
Social Science Research Network
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This article discusses the Windle and Carvalho's (2014) state-space model for observations and latent variables in the space of positive symmetric matrices. ...
The present discussion focuses on the model specification and on the contribution to the positive-value time series literature. ...
in the background section, a discussion on the inferential di culties that one might encounter in multivariate stochastic volatility modeling. ...
doi:10.2139/ssrn.2535282
fatcat:2mxueph5krc3tgnrl6beaf4coi
A Physical Analysis of Polarimetric SAR Data Statistical Models
2016
IEEE Transactions on Geoscience and Remote Sensing
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Statistical analysis of the simulated data shows that the distribution of the scatterer response has an effect only when the number of scatterers in a resolution cell is very small, which appears in very ...
The mixture of point targets and distributed targets will lead to an extremely heterogeneous appearance, which may be a clue to analyze the urban areas in polarimetric SAR data. ...
-2 data provided in the framework of the AgriSAR 2009 campaign, the Japan Aerospace Exploration Agency (JAXA) for the ALOS-2 data provided in the framework of the 4th ALOS Research Announcement for ALOS ...
doi:10.1109/tgrs.2015.2510399
fatcat:m4jbkazrgfgargtprjocs5jo7i
Origin of the dust bunny distribution in ecological community data
2015
Plant Ecology
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The distribution of sample units in multivariate species space typically departs strongly from the 1 multivariate normal distribution. ...
Dust bunny 16 intensity depends not only on population processes and disturbance, but also on the properties of the 17 sample, such as sample unit area or volume. 18 19 20 21 Our goals diverge from studies ...
We thank contributors of data; students and colleagues for helpful discussion; Dave Roberts for sharing a draft chapter on schools of community ecology, Amy Charron for dust bunny drawings, and Stéphane ...
doi:10.1007/s11258-014-0404-1
fatcat:4n6uldhgdjfjjgs32urcgmxjbe
Stochastic Newton Sampler: The R Package sns
2016
Journal of Statistical Software
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The R package sns implements Stochastic Newton Sampler (SNS), a Metropolis-Hastings Monte Carlo Markov Chain algorithm where the proposal density function is a multivariate Gaussian based on a local, second-order ...
When initial point is far from density peak, running SNS in non-stochastic mode by taking the Newton step -augmented with line search -allows the MCMC chain to converge to high-density areas faster. ...
Discussion In this paper we presented sns, an R package for Stochastic Newton Sampling of twicedifferentiable, log-concave PDFs, where a multivariate Gaussian resulting from second-order Taylor series ...
doi:10.18637/jss.v074.c02
fatcat:xnmwj4z72rc7xnvf3bwy76x5ha
Integrative analysis of time course metabolic data and biomarker discovery
[article]
2018
arXiv
pre-print
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of the multivariate information intrinsic to the data or iv) unable to uncover multiple associations between different omic data. ...
by augmenting the mixed-effects model with a conditional auto-regressive (CAR) component and iv) identify potential associations between heterogeneous omic variables . ...
The DPPCA model is a multivariate model using PCA, where PCA scores are modeled via a stochastic volatility model. ...
arXiv:1801.07767v2
fatcat:daea5fytobfdxcpzkrdeiprdc4
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