search for: normfit

Hi everybody, I wonder if there is a built-in function similar to Matlab's "normfit" which computes 95% CI based on the normality assumption. So, I have a vector of values and I want to calculate 95% normal CI. Of course, I could write my own function, no problem, but I still wonder if built-in functionality exists. (I wish quantile() had this functionality included). Anyone...

i want to plot the histogram and the curve in the same graph.if i have a set of data ,i plot the histogram and also want to see what distribution it was.So i want to plot the curve to know what distribution it like. -- View this message in context: http://www.nabble.com/how-to-plot-the-histogram-and-the-curve-in--the-same-graph-tp20082506p20082506.html Sent from the R help mailing list archive at

...t;- sp500[,2] #only adjusted close n <- length(sp500) logr <- log(sp500[1:n-1] / sp500[2: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]...

...#only adjusted close n <- length(sp500) logr <- log(sp500[1:n-1] / sp500[2:n]) acf(logr) 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]...