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Change point in variance of fractionally integrated noise
This paper studies the quasi-maximum likelihood estimator (quasi-MLE) of a change point in variance for the fractionally integrated noise with memory...
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Wild bootstrap Ljung–Box test for residuals of ARMA models robust to variance change
Ljung–Box (LB) test is one of the most popular test for determining whether autocorrelations in residuals of fitted time series models exist or not....
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Factorial Analysis of Variance (ANOVA)
Many empirical studies involve two or more independent variables. Analysis of variance (ANOVA) can easily be extended to these situations, and in...
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Variance Control Procedures
This chapter covers the concepts of variance and sources of variation for clinical trial data. Common metrics to quantify the extent of variability...
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Variance Reduction
The Monte Carlo methods described in the previous chapters are subject to variation due to the randomness inherent in sample generation. Ideally we...
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The estimated causal effect on the variance based on the front-door criterion in Gaussian linear structural equation models: an unbiased estimator with the exact variance
In this paper, we assume that cause–effect relationships between random variables can be represented by a Gaussian linear structural equation model...
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The distribution of the sample correlation coefficient under variance-truncated normality
The non-null distribution of the sample correlation coefficient under bivariate normality is derived when each of the associated two sample variances...
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Variance matrix estimation in multivariate classical measurement error models
Measurement errors are often encountered in several continuous variables in a data set, and various methods have been proposed to handle these...
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A Variance-Based Sensitivity Analysis Approach for Identifying Interactive Exposures
Chemical mixtures can significantly affect human health, but understanding the interactions among various chemical exposures and identifying...
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Scan Statistics for Detecting a Local Change in Model Parameters for Normal Data
In this chapter, we review the testing procedures that have been investigated in the scientific literature for detecting a local change in the...
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Scan Statistics for Detecting a Local Change in Model Parameters for Normal Data
In this chapter, we review the testing procedures that have been investigated in the scientific literature for detecting a local change in the...
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Generalized Bayes Minimax Estimators of the Variance of a Multivariate Normal Distribution
The problem of estimating the variance of a multivariate normal distribution is considered under quadratic loss. A large class of generalized Bayes...
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A Monte Carlo permutation procedure for testing variance components in generalized linear regression models
Testing zero variance components is of utmost importance in various applications empowered by the use of mixed-effects models. Focusing on...
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Robust Response Transformations for Generalized Additive Models via Additivity and Variance Stabilization
The AVAS (Additivity And Variance Stabilization) algorithm of Tibshirani provides a non-parametric transformation of the response in a linear model...
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Regression Analysis and the Analysis of Variance
In this chapter, we provide derivations of the formulas for simple and multiple linear regression. In obtaining these results, the partitioning of...
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DDCAL: Evenly Distributing Data into Low Variance Clusters Based on Iterative Feature Scaling
This work studies the problem of clustering one-dimensional data points such that they are evenly distributed over a given number of low variance...
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Frequentist Conditional Variance for Nonlinear Mixed-Effects Models
Nonlinear mixed-effects models are commonly used in fisheries and ecological studies to account for complex relationships and dependencies in data....
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Dismemberment and Design for Controlling the Replication Variance of Regret for the Multi-Armed Bandit
The multi-armed bandit problem refers to the task of sequentially assigning treatments to experimental units so as to identify the best treatment(s)...
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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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A Monte Carlo permutation procedure for testing variance components using robust estimation methods
Permutation methods offer an acceptable and convenient tool for inferring zero variance components in linear mixed models using the likelihood ratio...
