<--- Back to Details
First PageDocument Content
Econometrics / Parametric statistics / Time series analysis / Linear regression / Autoregressive conditional heteroskedasticity / Fisher information / Ordinary least squares / Maximum likelihood / Kalman filter / Statistics / Estimation theory / Regression analysis
Date: 2015-03-10 14:57:19
Econometrics
Parametric statistics
Time series analysis
Linear regression
Autoregressive conditional heteroskedasticity
Fisher information
Ordinary least squares
Maximum likelihood
Kalman filter
Statistics
Estimation theory
Regression analysis

Microsoft Word - DYNAMIC CONDITIONAL BETA[removed]

Add to Reading List

Source URL: vlab.stern.nyu.edu

Download Document from Source Website

File Size: 1,15 MB

Share Document on Facebook

Similar Documents

Graham Neubig – Non-parametric Bayesian Statistics Non-parametric Bayesian Statistics Graham Neubig

DocID: 1uQOM - View Document

Automatic Selection of Compiler Options Using Non-parametric Inferential Statistics Masayo Haneda Peter M.W. Knijnenburg Harry A.G. Wijshoff

DocID: 1tDtm - View Document

Proceedings of the 60th ISI World Statistics Congress, 26-31 July 2015, Rio de Janeiro, Brazil p.3981 Parametric or nonparametric: the FIC approach for stationary time series Gudmund Horn Hermansen*

DocID: 1tnWq - View Document

Statistics / Regression analysis / Estimation theory / Parametric statistics / Least squares / Linear regression / Ordinary least squares / Incremental validity / SAT / University of California / Variance / T-statistic

Microsoft Word - satpaper.forjoe.finalrevision.doc

DocID: 1rnIq - View Document

Statistics / Estimation theory / Regression analysis / Statistical theory / Parametric statistics / Signal processing / Ordinary least squares / Autocorrelation / Estimator / Generalized method of moments / Robust statistics / Linear regression

On the finite sample properties of pre-test estimators of spatial models Gianfranco Piras∗ Ingmar R. Prucha†

DocID: 1rm2t - View Document