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Variance function
Generalized Linear Models and Generalized Additive Models
Stochastic Process - Introduction
Variance Function Regressions for Studying Inequality
Flexible Signal Denoising Via Flexible Empirical Bayes Shrinkage
Variance Function Estimation in Multivariate Nonparametric Regression by T
Variance Function Program
Examining Residuals
Estimating Variance Functions for Weighted Linear Regression
Variance Function Regressions for Studying Inequality
Profiling Heteroscedasticity in Linear Regression Models
Variance Function Regressions for Studying Inequality
Wavelet-Based Functional Mixed Models
CHAPTER 6 Generalized Linear Models
Generalized Linear Models I
Effect of Mean on Variance Function Estimation in Nonparametric
Variance Function Estimation in Multivariate Nonparametric Regression
Generalized Linear Models
Stat 6550 (Spring 2016) – Peter F. Craigmile Introduction to Time Series Models and Stationarity Reading: Brockwell and Davis
Top View
Adaptive Variance Function Estimation in Heteroscedastic
Glms: Generalized Linear Models
Generalized Linear Models and Generalized Additive Models
Chapter 7: Modelling the Variance As a Function of Explanatory Variables
Ch. 6 Stochastic Process
Functional Variance Processes
Evaluation of Generalized Variance Function Estimators for the U.S
Some Refinements on the Comparison of Areal Sampling
An Introduction to Generalized Linear Models
Analysis of Generalized Variance Function Estimators from Complex Sample Surveys October 2013
Generalized Linear Models the General Linear Model Approach Used So Far
Smoothing Spline Estimation of Variance Functions
Weighted and Generalized Least Squares
Wavelet Methods Article ID
Addressing Margins of Error in Small Areas of Data Delivered Through the American Factfinder of the Census Transportation Planning Products Program
Assessing the Adequacy of Variance Function in Heteroscedastic Regression Models Lan Wang University of Minnesota,
[email protected]
Logistic Regression and Generalized Linear Models
See Pp1-17 2 Stationary Processes and Time Series I
Simultaneous Mean-Variance Regression
1 Central Tendency: Mode, Mean and Median
Estimation of Variance
Nonparametric Estimation of Genewise Variance for Microarray Data1
Stat 579: Generalized Linear Models and Extensions
Central Tendency, Variance, and Variability
Adaptive Variance Function Estimation in Heteroscedastic Nonparametric Regression
Lecture 12 Heteroscedasticity
Part IV: Theory of Generalized Linear Models
Error Variance Estimation in Nonparametric Regression Models
Introduction to Generalized Linear Models
15 Generalized Linear Models
Time Series Analysis
Second-Order Least Squares Estimation in Regression Models with Application to Measurement Error Problems
Estimation of Nonlinear Autoregressive Models Using Design-Adapted Wavelets*
Density Estimation Using Quantile Variance and Quantile-Mean Covariance
Applications of Distance Correlation to Time Series
Variance Function Estimation in High-Dimensions
Design Effects and Generalized Variance Functions for the 1990-91 Schools and Staffing Survey (SASS)
Stat 520 Forecasting and Time Series
STAT331 1-Sample Problem: Confidence Intervals for Quantiles
Chapter 9: Regression Diagnostics
Time Series Analysis: Forecasting and Control
Predictive Comparisons, Weighted Least Squares, Heteroskedasticity, Local Polynomial Regression
Conditional Variance Estimation in Heteroscedastic Regression Models
Forecasting Non-Stationary Time Series by Wavelet Process Modelling