search for: t_fit

...:n]) acf(logr) ar5 <- arima(logr, order = c(5, 0, 0), include.mean = T) logr<- ar5$res acf(logr) #fit GARCH distribution hist(logr, freq = F, ylim = c(0, 12), breaks = 'FD') norm_fit <- normFit(logr) curve(dnorm(x, norm_fit$est[1], norm_fit$est[2]), -.15, .15, add = TRUE, col=2) t_fit <- stdFit(logr) curve(dstd(x, t_fit$est[1], t_fit$est[2], t_fit$est[3]), -.15, .15, add = TRUE, col=6) snorm_fit <- snormFit(logr) curve(dsnorm(x, snorm_fit$est[1], snorm_fit$est[2], snorm_fit$est[3]), -.25, .15, add = TRUE, col=4) st_fit <- sstdFit(logr) curve(dsstd(x, st_fit$est[1], st...

...) ar5 <- arima(logr, order = c(5, 0, 0), include.mean = T) logr<- ar5$res #remove mean acf(logr) #fit GARCH distribution hist(logr, freq = F, ylim = c(0, 12), breaks = 'FD') norm_fit <- normFit(logr) curve(dnorm(x, norm_fit$est[1], norm_fit$est[2]), -.15, .15, add = TRUE, col=2) t_fit <- stdFit(logr) curve(dstd(x, t_fit$est[1], t_fit$est[2], t_fit$est[3]), -.15, .15, add = TRUE, col=6) snorm_fit <- snormFit(logr) curve(dsnorm(x, snorm_fit$est[1], snorm_fit$est[2], snorm_fit$est[3]), -.25, .15, add = TRUE, col=4) st_fit <- sstdFit(logr) curve(dsstd(x, st_fit$est[1], st...

...es for a fitted location, scale, and degrees of freedom of a dataset. I have no errors with the code however the estimates are not identical to the estimates I am getting when using SAS and MatLab (both give me the same estimates). Can someone comment on it? Here is the simple two lines I am using t_fit <- stdFit(independent) est <- t_fit$est where independent is my data to be fitted. Thanks! Alex -- View this message in context: http://www.nabble.com/stdFit-tp17018969p17018969.html Sent from the R help mailing list archive at Nabble.com.