coef

Info = data. frame (sapply (Model, function (A) coef (A$model))); names (Info) = "coef" row. names (Info) = names (Model)

Climate Audit 2009

Info = data. frame (sapply (Model, function (A) coef (A$model))); names (Info) = "coef" row. names (Info) = names (Model)

Climate Audit 2009

Original caption: “The frequency distribution of simulated climate sensitivity using all model versions (black), all model versions except those with perturbations to the cloud-to-rain conversion threshold (red), and all model versions except those with perturbations to the entrainment coef fi cient (blue).”

AGU Day 3 part C: How good are predictions from climate models? | Serendipity 2010

I suspect it may come from Hansen87 which calculated a correlation coef for pairs of stations

Unthreaded #19 « Climate Audit 2007

Statistical inference The regression model Estimating the model The OLS estimator Hypothesis testing The variance of the OLS estimator When the assumptions break down Background reading The variance-covariance matrix of β ˆ We'll generally want to ask questions about single coef fi cients in the model-e. g, is β2 different from zero?

Recently Uploaded Slideshows thaddunning 2010

For the 50 random variables in the design matrix, in expectation, the coef fi cients on 5 will be signi fi cant at the 0.1 level.

Recently Uploaded Slideshows thaddunning 2010

The Beauty in Numbers 35 If, by now, the students didn't see the connection, highlight the coef fi cients and the constants.

Recently Uploaded Slideshows sahmozac 2010

The model plays a key role: our estimates of coef fi cients and their standard errors, and associated signi fi cance tests, are all conditional on the model.

Recently Uploaded Slideshows thaddunning 2010

Algebraic Entertainments 115 A summary chart reveals a pattern among the coef fi cients of:

Recently Uploaded Slideshows sahmozac 2010

Statistical inference The regression model Estimating the model The OLS estimator Hypothesis testing The variance of the OLS estimator When the assumptions break down Background reading Standard errors in the bivariate case In a bivariate regression, the standard error of the estimated slope coef fi cient is the square root of the (2,2) element of σ2

Recently Uploaded Slideshows thaddunning 2010