similar to: lmomco package - Random number generation using Wakeby distribution

Hi, I am using parnor function of lmomco package. I believe it provides mean and std. dev for the set of data. But the std. dev provided does not match with the actual std. dev of the data which is 247.9193 (using sd function). Am I missing something here? > lmr <- lmom.ub(c(123,34,4,654,37,78)) > parnor(lmr) $type [1] "nor" $para [1] 155.0000 210.2130 >

Hi guys, I'm trying to use lmomco package. first I did the manual calculation on what is the estimates scale and location parameter given L-CV=0.2, L1=1000 L-moments and k (shape parameter) =- 0.1. so what i get is: location: 821.0445 scale: 260.7590 shape: -0.1000 #I assign this as GEV vectors using vec2par GEVpara2<-vec2par(c( 821.0445 , 260.7590 ,-0.1),'gev') #then I

Hello, I am using the lmomco package (lmom.ub and pargev) to compute the GEV parameters (location, scale, and shape), which are used to estimate return values. I was wondering how/if I can calculate upper and lower confidence (CI_u, CI_l) intervals for each return frequency using the GEV parameters to fill-in the table below? Xi (location) = 35.396 Alpha (scale) = 1.726 Kappa (shape) =

CRAN et al., I would like to add an extented introduction or other arbitrary sections to my package lmomco. I have been shipping inst/doc/Introduction.Rd. I would like to have this content inserted to the front of the PDF build for the CRAN. The R-exts.pdf seems to be a little silent on this subject? For my purposes, I have been doing this R CMD Rd2dvi --pdf

Dear R forum, I am bit confused and please guide me - (1) Is "Pearson Type III Distribution" as given in lmomco package same as Three Parameter Pearson 5 Distribution? If not, how do I estimate the parameters of Three Parameter Pearson 5 Distribution? (2) Is there any other R forum dealing with only Statistical queries? Kindly guide Regards Katherine [[alternative HTML version

Hi, I have a data set which is assumed to follow weibull distr'. How can I find of cdf for this data. For example, for normal data I used (package - lmomco) >cdfnor(15,parnor(lmom.ub(c(df$V1)))) Also, lmomco package does not have functions for finding cdf for some of the distributions like lognormal. Is there any other package, which can handle these distributions?

Dear R helpers, I am not a statistician and right now struggling with Richards curve. Wikipedia says (http://en.wikipedia.org/wiki/Generalised_logistic_function) The "generalized logistic curve or function", also known as Richard's curve is a widely-used and flexible sigmoid function for growth modelling, extending the well-known logistic curve. Now I am confused and will like to

Hi R-users, I'm trying to repeat the same procedure to 1000 data set. I know this is very easy, but I got stuck finding the right and fastest way in running it. IID50=Riidf[1:50,1:1000] #where IID50 is a dataframe consist of 1000 time series(as column) and 50 time scales (row). #what I tried to do: estIID50=rep(NA,1000) for (i in 1:1000) estIID50[i]=pargev(lmom.ub(IID50[1:50,i])) #warning

Hi! Unfortunately the version loaded on the office server is 2.6.0 (for some undisclosed so called policy decision by my adamant IT dept. who are not willing to upgrade), I need to use YieldCurve package compatible with this version. On my standalone machine I have R 2.9 loaded and hence I have no problem in using the YieldCurve package. (a) Kindly guide how do I download the version of

I upgraded to R-2.2.1 on two PPC G5 computers today. Further I want to work with the tseries package for the first time. As root with R CMD INSTALL tseries_0.10-0.tar.gz I get the following gcc-3.3 -bundle -flat_namespace -undefined suppress -L/usr/local/lib - o tseries.so arma.o bdstest.o boot.o dsumsl.o garch.o ppsum.o tsutils.o -framework vecLib -L/usr/local/lib/gcc/powerpc-apple-

Hi, Could someone please suggest where I might find some instructions / tutorials / FAQs that describe how to create a frequency distribution and cumulative frequency distribution in R using different class withs. I have about a 2-million observations (distances between points ranging from sub-millimetre to about 400km, and I want to get a feel for how they are distributed). I'd like the

Dear all, I wanna to do multiple comparison test for proportions (multiple chi squre ?), could someone tell me how in R, thank you!

the backage lmomco can plot the L-moments ratio diagram would it be possible to draw the TL moments diagram also? -- Osama Abdelaziz Hussien Department of Statistics Faculty of Commerce Alexandria University Egypt

Respected Sir I have to select a probability distribution using L-moment Ratio Diagram. I am not understanding how to plot sample TAU3 and TUA4 on L-moment Ratio Diagram. Please Guide me Best Regards -- AMINA SHAHZADI Department of Statistics GC University Lahore, Pakistan. Email: amnakhan493@gmail.com amna_989@hotmail.com amna_989@yahoo.com [[alternative HTML version deleted]]

Deal list > I want to generate a random number in an interval using exponential low > I know how to make that simply using uniform low > x1 <- runif(1, 5.0, 7.5) > this will generate a number between 5 et 7.5 but with uniform low. > Could you help pease.? > Regards > > -- > PhD candidate in Computer Science > Address > 3 avenue lamine, cité ezzahra, Sousse 4000

Dear Sir I am getting errors in using following R code for L-moment ratio diagram Help in this regard > "plotlmrdia" <- + function(lmr, + nopoints=FALSE, + nolines=FALSE, + nolimits=FALSE, + nogev=FALSE, + noglo=FALSE, + nogpa=FALSE, + nope3=FALSE, + nogno=FALSE, + noexp=FALSE, + nonor=FALSE, +

Dear All, When I plot the values and linear regression line for one data set, it is fine. But for another one I see zigzags, when I plot the confidence interval >cd Depth CHAOsep12RNA 9,94 804 25,06 1476,833333 40,04 1540,561404 50,11 1575,166667 52,46 349,222222 54,92 1941,5 57,29 1053,507042 60,11 1535,1 70,04 2244,963303 79,97 1954,507042 100,31 2679,140625 >

Dear R users, I'd like to known your opinion about a problem with anova.lmRob() of "Robust" package that occurs when I run a lmRob() regression on my dataset. I check my univariate model by single object anova as anova(lmRob(y~x)). If I compare my model with the null model (y~1), I must obtain the same results, but not for my data. Is it possible? My example:

I'm sorry, maybe the question was bad posed. Ista has well described my problem. Thanks Massimo >----Messaggio originale---- >Da: izahn at psych.rochester.edu >Data: 28/07/2011 17.52 >A: "David Winsemius"<dwinsemius at comcast.net> >Cc: "m.fenati at libero.it"<m.fenati at libero.it>, <r-help at r-project.org> >Ogg: Re: [R]

Hi, Sorry for the naive question, but what exactly does the 'Adjusted R-squared' coefficient in the summary of linear model adjust for? Sample code: > x <- rnorm(15) > y <- rnorm(15) > lmr <- lm(y~x) > summary(lmr) Call: lm(formula = y ~ x) Residuals: Min 1Q Median 3Q Max -1.7828 -0.7379 -0.4485 0.7563 2.1570 Coefficients: