search for: contiuous

Hi; I would like to fit a contiuous right skewed dist. to a set of data. So, I want to use MLE or Robust estimation of the parameters, then use A-D or K-S test or Robust alternative for the goodness-of -fit. Also I would rank the fitted distributions according to the p-value of the test. Does anyone know how I do this in R. any backa...

...; by maximum likelihood Parameters : estimate Std. Error size 0.3397148 0.03775577 mu 1.7787630 0.16429774 Loglikelihood: -701.0615 AIC: 1406.123 BIC: 1414.16 ------ I am wondering how to translate the size and the mu parameter into the usual number of successes (n) and the contiuous probability (p) . To me it is not clear what these mu and size parameter declares. Help is appreciated Best Alex [[alternative HTML version deleted]]

for a silly question, wondering how to test fit with the one sample as follow. I have read _fitting distributions with R_, but that doesn't answer my specific question. inclined to use Kolmogorov-Smirnov D, and its associative p value. much appreciation! X20.001 232 93 84 185 336 417 228 199 2110 1411 612 1913 1314 3015

Hi - I'm just starting out with R and have come up against a problem with what should be a simple operation. I'm plotting a range of safety standards for 7 different chemicals. I don't want the standard box and whisker plot - I just a dot for each value. Whilst using "plot.default" I get the error "invalid xlim value" - which is confusing since using the same script

Dear list: I am attempting to use what I thought would be a pretty straightforward practical application of Cox regression. I figure users of the survival package must have come across this problem before, so I would like to ask you how you dealt with it. I have set up an illustrative example and included it at the end of this post. I took a sample of 100 data points from each of two populations