similar to: Hi~problem with the two sample test: ks2Test in the package of fbasics

Dear all, I am trying to use the rstable(n, alpha, beta, gamma = 1, delta = 0, pm = c(0, 1, 2))) function to generate positive stable random numbers. For positive stable distribution, beta==1 and alpha is in (0,1), which defines random variables with support (0, infinity). So, I used rstable(100, 0.5, 1) for an example. I found that this gives me some negative numbers. For example, >

hi, I have installed the fbasics package. And when I wrote "?stablefit", it says 'No documentation for 'stablefit' in specified packages and libraries'. When I tried "??stablefit", it showed that the stablefit is in fBasics::Distributionfit. However, I have installed the fbasics package. I don't know how to solve this problem. Could anyone help me? Thank

Hello I do not know very much about statistics (and English language too :-( ), then I come in search of a clarification (explanation): I found two distinct results on KURTOSIS and I do not know which of them is the correct one. Any aid will be welcome! klebyn ################ CODE rnorm(1000) -> x library(moments) kurtosis(x) skewness(x) detach("package:moments")

Hello, I've been trying to install the fBasics package on an openSuSe 11.3 64bit machine. It gives an error saying: WARNING: *R* *include* *directory* *is* *empty* -- *perhaps* *need* *to* *install* *R*-*devel*.*rpm* *or* similar Yet, R-devel is installed. Other packages work fine. I also tried different ways to install...install.packages() and R CMD INSTALL... The complete message is

Dear R People: There is a function from the fBasics library to get the probability and quantiles for the hyperbolic probability function. Is there one that will estimate parms of the hyperbolic probability function from a data set, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R Version 2.0.1 windows

fBasics question: Get maximum dates Hello, This two series data set has been created with the timeSeries() function from fBasics >str(total) Formal class 'timeSeries' [package "fBasics"] with 7 slots ..@ Data : num [1:262, 1:2] 8703 8603 8573 8680 8668 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:262] "2004-04-19 01:00:00"

Hi, I am trying to calculate probability density of normal inverse gaussian distribution. I am using dnig function of fBasics package. However, I am getting following result. The density at x = 0.003042866 is: > dnig(x= 0.003042866, alpha=5.184868, beta= 0.11841, delta= 0.06038513, mu= -0.0003520626) [1] 6.550251 I am not sure why it is 6.550251. Can anyone tell me why density is more than

Dear R users, I'm trying to fit stable distribution and hyperbolic distribution to my data using stableFit(), and hypFit() of fBasics. However, there are some problems This is the result ====================================== > stableFit(lm, alpha = 1, beta = 0, gamma = 1, delta = 0, doplot = TRUE, trace = FALSE, title = NULL, description = NULL) Title: Stable Parameter Estimation

I have a problem wirh R: After loding fBasics packages log funtion doesn't work like as fallow: Cenap ERDEMIR Hacettepe University Turkey > log(20) [1] 2.995732 > local({pkg <- select.list(sort(.packages(all.available = TRUE))) + if(nchar(pkg)) library(pkg, character.only=TRUE)}) Loading required package: fImport Loading required package: fSeries Loading required package: robustbase

Can anyone explain such different output: > stableFit(s,alpha = 1.75, beta = 0, gamma = 1, delta = 0, + type = c("q", "mle"), doplot = TRUE, trace = FALSE, title = NULL, + description = NULL) Title: Stable Parameter Estimation Call: .qStableFit(x = x, doplot = doplot, title = title, description = description) Model: Student-t Distribution Estimated

When I try to load "fBasics" package, I get following error/warning : > library(fBasics) Loading required package: fImport Loading required package: fSeries Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package:

Dear all, I am having difficulty interpreting the parameter estimates from the stablereg function. Specifically I am trying to keep things simple to start with by using stablereg to fit a normal distribution to a simulated data set from that distribution (in order to understand the way that stablereg reports parameter estimates). I cannot work out the scale on which the dispersion parameter (some

Hi, I have a problem with Kolmogorov-Smirnov test fit. I try fit distribution to my data. Actualy I create two test: - # First Kolmogorov-Smirnov Tests fit - # Second Kolmogorov-Smirnov Tests fit see below. This two test return difrent result and i don't know which is properly. Which result is properly? The first test return lower D = 0.0234 and lower p-value = 0.00304. The lower 'D'

Hi everybody, while performing ks.test for a standard exponential distribution on samples of dimension 2500, generated everytime as new, i had this strange behaviour: >data<-rexp(2500,0.4) >ks.test(data,"pexp",0.4) One-sample Kolmogorov-Smirnov test data: data D = 0.0147, p-value = 0.6549 alternative hypothesis: two.sided >data<-rexp(2500,0.4)

Is the kolmogorov-smirnov test valid on both continuous and discrete data? I don't think so, and the example below helped me understand why. A suggestion on testing the discrete data would be appreciated. Thanks, a <- rnorm(1000, 10, 1);a # normal distribution a b <- rnorm(1000, 12, 1.5);b # normal distribution b c <- rnorm(1000, 8, 1);c # normal distribution c d <- rnorm(1000,

I am trying to determine whether two samples are identical or not. I'm aware that somebody can use the Kolmogorov-Smirnoff test to compare empirical distributions, but since my samples have ties I'm not sure if I'm getting the right p-values for the comparison. Can the Kolmogorov-Smirnoff test be adjusted for the case when ties exists and are there any functions that already

I got a distribution function and a empirical distribution function. How do I make to Kolmogorov-Smirnov test in R. Lets call the empirical distribution function >Fn on [0,1] and the distribution function >F on [0,1] ks.test( ) thanks for the help -- View this message in context: http://www.nabble.com/Kolmogorov-Smirnov-test-tp23296096p23296096.html Sent

Hi, Interpretation problem ! so what i did is by using the: >fit1 <- fitdist(vectNorm,"beta") Warning messages: 1: In dbeta(x, shape1, shape2, log) : NaNs produced 2: In dbeta(x, shape1, shape2, log) : NaNs produced 3: In dbeta(x, shape1, shape2, log) : NaNs produced 4: In dbeta(x, shape1, shape2, log) : NaNs produced 5: In dbeta(x, shape1, shape2, log) : NaNs produced 6: In

Hi, why don't you try try ks.test(VeriSeti1, VeriSeti2)$p.value All the best Jenny >How can i print only the P-Value of the kolmogorov smirnov test? > > >> ks.test(VeriSeti1, VeriSeti2) > > Two-sample Kolmogorov-Smirnov test > >data: VeriSeti1 and VeriSeti2 >D = 0.5, p-value = 0.4413 >alternative hypothesis: two-sided > > >This expression

Hi. On all of my machines, except for a netbook cursed with the GMA500 chipset, the R packages are synced to lenny-cran. I have been using rpy in a chroot using the official lenny R packages (2.7.1) given that i have not been able to find compatible rpy deb packages to work with lenny-cran. I am able to build the rpy deb package from source in a 32-bit lenny chroot (with the stock R packages)