Nothing
fitLinearAndStorage<-function(data_in, ldata_out, start_ind, temp3, R){
###########################################
# Fit a linear model #
###########################################
glm.linear<-glm(ldata_out ~ data_in)
# Find the AIC value associated with the linear model
AIC1 = AIC(glm.linear)
# Storage for the linear model
R[start_ind,21] = glm.linear$coefficients[[2]] # Slope coefficient
R[start_ind,71] = glm.linear$coefficients[[1]] # intercept coefficient - for output to user later on
# Isolate the standard errors for the linear model
SEs = sqrt(diag( vcov(glm.linear)))
R[start_ind,22] = SEs[[2]] # SE of slope
# Find the mean of the data for calculation of the R2 value of linear model
mean1 = mean(ldata_out)
R[start_ind,23] = 1 - sum(residuals(glm.linear)^2)/sum((ldata_out-mean1)^2) # R2 value for linear model
R[temp3, 24] <-fitted.values(glm.linear) # Store fitted values
R[temp3, 25] <- residuals(glm.linear) # Store residual values
if (length(data_in)>3){
R[temp3, 26] <-ls.diag(glm.linear)$stud.res # Store student residual values
R[temp3,27] <-ls.diag(glm.linear)$std.res # Store standardised residual values
}
R[start_ind, 28] <-summary.glm(glm.linear)$coefficients[[2,4]] # Store p-value associated with slope in linear model
R[start_ind,29] = AIC1 # Store AIC for linear model
return(list(glm.linear = glm.linear, R=R, AIC1 = AIC1))
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.