graphing the normal distribution
David White <dwhite at ling.ohio-state.edu> writes:
Hello, I'd like to make some simple example graphs of the normal distribution, varying standard deviation, mean, and kurtosis across examples. I have been able to manipulate mean and sd using rnorm and hist: y_hist(rnorm(1000000, mean=100, sd=50), 50, plot=F) plot(y$mid,y$count,type="l") Two questions: 1) n=100000 seems like a lot of samples to approach a smooth curve. Is there a way to make the curve smooth, but computationally less demanding?
Perhaps curve(dnorm(x,mean=0,sd=1),from=-3,to=3) etc.?
2) What can I do to change the "peakiness" of the distribution?
Nothing within the Normal distribution family since it has constant shape... the t-distributions have bigger kurtosis for given variance as far as I recall, and uniform distributions have less. (Don't shoot me if I got that wrong, it's not like I need to use it every day.)
O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._