<--- Back to Details
First PageDocument Content
Regression analysis / Bayesian statistics / Probit model / Probit / Likelihood function / Maximum likelihood / Normal distribution / Statistics / Estimation theory / Single equation methods
Date: 2006-08-23 10:23:44
Regression analysis
Bayesian statistics
Probit model
Probit
Likelihood function
Maximum likelihood
Normal distribution
Statistics
Estimation theory
Single equation methods

Add to Reading List

Source URL: ses.telecom-paristech.fr

Download Document from Source Website

File Size: 94,45 KB

Share Document on Facebook

Similar Documents

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

DocID: 1v2C1 - View Document

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

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

DocID: 1u6YM - View Document