The generalized-least-squares tag has no wiki summary.
3
votes
0answers
45 views
Generalised least squares: from regression coefficients to correlation coefficients?
For least squares with one predictor:
$y = \beta x + \epsilon$
If $x$ and $y$ are standardised prior to fitting (i.e. $\sim N(0,1)$), then:
$\beta$ is the same as the Pearson correlation ...
4
votes
1answer
78 views
Weighted least squares regression on random data, giving large t-statistics more often than “expected”
My question is about the distribution of the t-statistics in Weighted Least Squares regression.
I'm finding that for a fixed Y and random ...
2
votes
1answer
170 views
Bayesian approach and least-squares approach to multivariate regression with structural design
Assume for example a trivariate Gaussian model:
$$
{\boldsymbol Y}_1, \ldots, {\boldsymbol Y}_n \sim_{\text{iid}} {\cal N}_3\left({\boldsymbol \mu}, \Sigma\right) \quad (*)
$$
with ${\boldsymbol \mu} ...
1
vote
1answer
162 views
Significance of the component in a multivariate linear model (“within-design”)
I'm trying to test the significance of the "component" effect in a multivariate regression model. I'm not sure what is the right way. Using R, I have tried a way with ...
1
vote
0answers
104 views
Prediction for one-way random effect ANOVA with rms package
I'm trying to predict in the one-way random effect ANOVA model fitted with the Gls() function of the rms package. All my attempts are unsuccessful. For instance:
...
4
votes
1answer
184 views
LARS - LASSO with weights
I am interested in solving the following problem
$$ \min_{\boldsymbol{\beta}} \left( \mathbf{y}-\mathbf{X}\boldsymbol{\beta} \right)^T W \left( \mathbf{y}-\mathbf{X}\boldsymbol{\beta} \right) + ...
2
votes
1answer
295 views
Should I keep or remove random effects?
After attempting to produce a linear mixed model, I was left with a great deal of heterogeneity.
...
3
votes
2answers
830 views
Non-Correlated errors from Generalized Least Square model (GLS)
As a financial institution, we often run into analysis of time series data. A lot of times we end up doing regression using time series variables. As this happens, we often encounter residuals with ...
0
votes
2answers
209 views
Software for fitting generalized least squares model with errors that follow seasonal ARMA model
I need to fit a GLS model, with some known regressors, and where the errors follow an unknown ${\rm ARIMA}(1,0,1) \times (1,N,1)$ model. It seems like the main tool out there for such models is the ...
1
vote
1answer
171 views
Trend analysis in temperature time series
Does anyone know how to determine the significance of the slope from linear model fitted using generalised least squares (GLS)?
I am fitting a linear model to temperature time series with the aim of ...
1
vote
1answer
202 views
Are HAC estimators used for estimation of regression coefficients?
The references I can find on HAC procedures (like Newey-West) in regression focus on the standard error of the estimated regression coefficients and hypothesis testing involving the same. I cannot ...
