<--- Back to Details
First PageDocument Content
Numerical analysis / Regression analysis / Data analysis / Time series analysis / B-spline / Nonparametric regression / Smoothing / Akaike information criterion / Forecasting / Statistics / Splines / Interpolation
Date: 2005-10-07 17:56:42
Numerical analysis
Regression analysis
Data analysis
Time series analysis
B-spline
Nonparametric regression
Smoothing
Akaike information criterion
Forecasting
Statistics
Splines
Interpolation

Functional Coefficient Regression Models for Nonlinear Time Series: A Polynomial Spline Approach JIANHUA Z. HUANG University of Pennsylvania HAIPENG SHEN University of North Carolina at Chapel Hill

Add to Reading List

Source URL: www.stat.tamu.edu

Download Document from Source Website

File Size: 221,31 KB

Share Document on Facebook

Similar Documents

Analysis Regression Summary KDD CUP 2017: Volume Prediction Task Solution by CarTrailBlazer

Analysis Regression Summary KDD CUP 2017: Volume Prediction Task Solution by CarTrailBlazer

DocID: 1vaMX - View Document

Bounds on Treatment Effects in Regression Discontinuity Designs with a Manipulated Running Variable François Gerard, Miikka Rokkanen, and Christoph Rothe Abstract The key assumption in regression discontinuity analysis

Bounds on Treatment Effects in Regression Discontinuity Designs with a Manipulated Running Variable François Gerard, Miikka Rokkanen, and Christoph Rothe Abstract The key assumption in regression discontinuity analysis

DocID: 1v2C1 - View Document

Fully Bayesian analysis of allele-specific RNA-seq data using a hierarchical, overdispersed, count regression model Ignacio Alvarez Jarad Niemi

Fully Bayesian analysis of allele-specific RNA-seq data using a hierarchical, overdispersed, count regression model Ignacio Alvarez Jarad Niemi

DocID: 1uCLx - View Document

Vito Ricci - R Functions For Regression Analysis – R FUNCTIONS FOR REGRESSION ANALYSIS Here are some helpful R functions for regression analysis grouped by their goal. The name of packa

Vito Ricci - R Functions For Regression Analysis – R FUNCTIONS FOR REGRESSION ANALYSIS Here are some helpful R functions for regression analysis grouped by their goal. The name of packa

DocID: 1urip - View Document

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods  Lecture: 6 Dimensionality Reduction and Learning: Ridge Regression vs. PCA Instructor: Sham Kakade

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 6 Dimensionality Reduction and Learning: Ridge Regression vs. PCA Instructor: Sham Kakade

DocID: 1u6YM - View Document