The gls tag has no wiki summary.
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Comparing GLS models with different fixed variables using AIC: REML or ML?
I am using gls in nlme. My response variable is spatial so I am using gls with correlation structure. I am determining which structure to use based on Zuur 2009, comparing AIC scores of models with ...
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How to calculate the regression variance for a GLS model?
I need to calculate the regression variance ($\sigma^2$) in order to estimate both the confidence intervals and the prediction intervals in a gls regression analysis. For the analysis, the covariance ...
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Variance associated with factors in GLS (nlme)
First time posting here, so thank you ahead of time for your help. I'd like to estimate the variances associated with two factors in a relatively simple, but unbalanced GLS model, and I am unsure how ...
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GLS error in R - “Error in glsEstimate(glsSt, control = glsEstControl) : computed ”gls“ fit is singular, rank 16”
I'm attempting to follow the 'Protocol' as in Chapters 4 & 5 of Zuur et al 2009 for some data I have for a number of river sites, sampled once for macroinvertebrates. Each site has been graded ...
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Is there a serial autocorrelation test for FGLS-FE fitted with pggls function in R?
a simple question here: is there any AR1 and AR2 test for FGLS-FE fitted with the pggls function of plm package in R?
(one example would be the Baltagi-Wu LBI test)
Thanks for your attention!
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Generalized least squares with insignificant predictor variable
Suppose I have fitted an standard linear regression mode $Y=\beta_0+\beta_1X_1+\beta_2X_2+\beta_3X_3+\epsilon$. Based on the ACF plot or PACF plot of the residuals for this regreesion model, I found ...
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How to specify in r spatial covariance structure similar to SAS sp(pow) in a marginal model?
I'm currently translating existing code from SAS to R. I'm working on longitudinal data (CD4 count over time). I have the following SAS code :
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Can dredge() in R package MuMIn deal with global model objects generated by gls() in nlme?
I am trying to use the function dredge() in the package MuMIn to compare AIC model-selection statistics for models of all ...
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How to pass a weighting matrix to the gls function in the nlme package?
Let's assume that the residual covariance matrix $\sum$ is known. Then, if I understood it correctly, the GLS estimator should be the better choice (in comparison to OLS) and this estimator includes ...
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1answer
266 views
Robust standard error in generalized least squares regression
Suppose we have a correlated outcome $\mathbf{y}$ and a bunch of predictors $\mathbf{X}$. For some reason, we know the variance/covariance matrix of the error term $(\epsilon)$, say $\mathbf{V}$.
In ...
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1answer
177 views
Performing a GLS cross-sectional regression using R
Is there a function in R that could perform GLS cross-sectional regression for multiple cases all at once?
For example, when regressing stock returns over beta for 100 stocks over a 10-year time ...
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How to interpret these custom contrasts?
I am doing a one way ANOVA (per species) with custom contrasts.
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Robust version of GLS with regression weights in R?
Robust version of GLS with regression weights in R?
Hi all,
In the following webpage, I have expressed my concern about the heteroskedasticity in my residuals using rlm with regression weights in R:
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158 views
Evaluation of a GLS fit
My first post in this useful community. Ive been trying to use GLS methods in non-linear mixed effects models and have found this post, Prediction with GLS extremely informative and helpful.
Some of ...
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1answer
203 views
proof FGLS asymptotically efficient
Prove that FGLS is asymptotically efficient. Does one have to use Cramer Rao to do this?
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410 views
Can I use generalised least squares with a binomial distribution and a nested structure?
I'm trying to fit linear models to my data in R. I need to use a generalised least squares method as I have heterogeneity of variance in one of my variables. I was planning to use varIdent, as the ...
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174 views
Inference in linear model with conditional heteroskedasticity
Suppose I observe independent variable vectors $\vec{x}$ and $\vec{z}$ and dependent variable $y$. I would like to fit a model of the form:
$$y = \vec{x}^{\top}\vec{\beta_1} + \sigma ...
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452 views
Prediction with GLS
Let's say I build a Generalized Least Squares model. I follow the standard procedure and first estimate a LM model. Then I create an error-response covariance matrix based on the residuals of this ...
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1answer
349 views
How to get equivalent ANOVA in R for a model with and without a random effect?
My question is:
Is there a way to either force Anova() to somehow analyze gls objects (which internally are almost identical ...
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1answer
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Fitting a generalized least squares model with correlated data; use ML or REML?
Reading the Linear Mixed Model (LMM) literature I am aware that fitting a model using REML provides better estimates of variance parameters than fitting via ML. However, we should not compare nested ...
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260 views
Is there a GLS estimator that has lower variance than OLS for sum of parameters in linear model under Gauss-Markov conditions?
I have a model $$Y=\beta_0 + \beta_1 x_1 + \beta_2x_2 +\epsilon$$
I would like the minimum variance unbiased estimate of $\gamma=\beta_1 + \beta_2$. Assuming the Gauss Markov conditions hold, but ...
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297 views
Estimation of time series regression using GLS
I am trying to estimate time series model using gls method.
The data is monthly from sep 1997 to april 2011
First I estimate the model and know that the erorr are IMA(1,1). For that I use the code ...
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Difference between GLS and SUR
I've been reading some about Generalized Least Squares (GLS) and trying to tie it back to my basic econometric background. I recall in grad school using Seemingly Unrelated Regression (SUR) which ...
