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Advances in Maximum Likelihood Estimation of Fixed-Effects Binary Panel Data Models
We review recent fixed-effects approaches to the formulation and estimation of models for binary panel data, measured at T time occasions. We offer a...
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Optimal experimental design for linear time invariant state–space models
The linear time invariant state–space model representation is common to systems from several areas ranging from engineering to biochemistry. We...
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Surrogate Models for Optimization of Dynamical Systems
Surrogate models using a suitable orthogonal decomposition and radial basis functions have been proposed by many researchers to reduce the...
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Hidden Markov and Semi-Markov Models When and Why are These Models Useful for Classifying States in Time Series Data?
Hidden Markov models (HMMs) and their extensions have proven to be powerful tools for classification of observations that stem from systems with...
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Fixed versus Mixed Effects Based Marginal Models for Clustered Correlated Binary Data: an Overview on Advances and Challenges
In a cross-sectional cluster setup, the binary responses from the individuals in a cluster become correlated as they share a common cluster effect,...
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Profile quasi-maximum likelihood estimation for semiparametric varying-coefficient spatial autoregressive panel models with fixed effects
This paper aims to propose a profile quasi-maximum likelihood estimation method for semiparametric varying-coefficient spatial autoregressive(SVCSAR)...
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Dynamic Networks with Multi-scale Temporal Structure
We describe a novel method for modeling non-stationary multivariate time series, with time-varying conditional dependencies represented through...
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Assessing the numerical integration of dynamic prediction formulas using the exact expressions under the joint frailty-copula model
Joint models allow survival outcomes of a patient to be dynamically predictable based on intermediate events observed after treatment. The existing...
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Model averaging for semiparametric varying coefficient quantile regression models
In this study, we propose a model averaging approach to estimating the conditional quantiles based on a set of semiparametric varying coefficient...
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Jackknife empirical likelihood based diagnostic checking for Ar(p) models
Diagnostic checking is an important predefined step before using autoregressive models. Although many portmanteau tests were proposed for diagnostic...
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A sequential feature selection approach to change point detection in mean-shift change point models
Change point detection is an important area of scientific research and has applications in a wide range of fields. In this paper, we propose a...
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Empirical likelihood and estimation in varying coefficient models with right censored data
In this paper, the empirical likelihood and estimations problems in varying coefficient models with right censored data are investigated by using a...
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Bayesian nonparametric dynamic hazard rates in evolutionary life tables
In the study of life tables the random variable of interest is usually assumed discrete since mortality rates are studied for integer ages. In...
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Time Series and Dynamic Systems
When observations are not independent of each other, special methods are necessary for estimation and model-building. The Box-Jenkins approach is...
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A Tail Measure With Variable Risk Tolerance: Application in Dynamic Portfolio Insurance Strategy
Risk measures for tail risk have an important application in the dynamic portfolio insurance strategies. We propose a new risk measure called...
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Using reference models in variable selection
Variable selection, or more generally, model reduction is an important aspect of the statistical workflow aiming to provide insights from data. In...
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Homogeneity tests for one-way models with dependent errors under correlated groups
We consider the problem of testing for the existence of fixed effects and random effects in one-way models, where the groups are correlated and the...
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A Novel Framework and a New Score for the Comparative Analysis of Forest Models Accounting for the Impact of Climate Change
A broad consensus has been reached on the need to adapt the management of our forests to the context of the rapidly changing climate, which resulted...
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Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach
We present a method for parameter estimation for nonlinear mixed-effects models based on ordinary differential equations (NLME-ODEs). It aims to...
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Robust MAVE for single-index varying-coefficient models
In this paper, a robust, efficient and easily implemented estimation procedure for single-index varying-coefficient models is proposed by combining...
