similar to: Simulate negative skewed, fat-tailed distribution

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, >

Hello, I'm having trouble figuring out how to calculate a p-value for a 1-tailed test of beta_1 in a linear model fit using command lm. My model has only 1 continuous, predictor variable. I want to test the null hypothesis beta_1 is >= 0. I can calculate the p-value for a 2-tailed test using the code "2*pt(-abs(t-value), df=degrees.freedom)", where t-value and degrees.freedom

How do we get 2-tailed p-values for the rlm summary? I'm using the following: > fit <- rlm(oatRT ~ oatoacData$erp, psi=psi.bisquare, maxit=100, na.action='na.omit') > fitsum <- summary(fit, cor=F) > print(fitsum) Call: rlm(formula = oatRT ~ oatoacData$erp, psi = psi.bisquare, maxit = 100, na.action = "na.omit") Residuals: Min 1Q Median

I am trying to find a definition for the two-tailed exact binomial test but have been unsuccessful. Can you help? --------------------------------- [[alternative HTML version deleted]]

Full_Name: Gael Millot Version: 2.2.0. OS: XP Submission from: (NULL) (195.220.102.20) Hello. I sent an Email in r-help without answer for the moment. I am wondering if it could have a mistake in the code of the ansari.test function. For me, it seems that the function do not recover the p value at the correct side of the normal law N(0, 1) when it use the normal approximation (presence of

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 everyone, when I use the two sample Kolmogorov¨CSmirnov ks2Test like this: x=read.table("e:/x.txt") y=rstable(1000,alpha,beta,gamma,delta) I alway get results as follows: Warning messages: 1: In ks.test(x = x, y = y, alternative = "two.sided") : cannot compute correct p-values with ties 2: In ks.test(x = x, y = y, exact = TRUE, alternative = "two.sided")

Hello all, I need to simulate rating scale from skewed and kurtosis. I would like to simulate a set of (discrete) data. ( n=1000, Item = 50 and 5 choice (1-5) ) Regards, Vichr -- View this message in context: http://r.789695.n4.nabble.com/How-to-simulate-rating-scale-from-skewed-and-kurtosis-tp4363805p4363805.html Sent from the R help mailing list archive at Nabble.com.

Hello. I am probably wrong... I am wondering if it could have a mistake in the code of the ansari.test function. For me, it seems that the function do not recover the p value at the correct side of the normal law N(0, 1) when it use the normal approximation (presence of ties) in a one tailed test. Exemple : quanti<-c(197, 205, 228, 234, 237, 195, 233, 226, 244, 227, 259, 185, 198, 253, 207,

Hello, I need a specific version of R installed for consistency reasons. I do the standard setup steps: echo "deb https://cran.ma.imperial.ac.uk/bin/linux/ubuntu trusty/" | sudo tee -a /etc/apt/sources.list sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9 sudo apt-get update And then a simple install call, which used to work just fine some time ago, tosses an

I have a R script that I call from python using rpy2. It uses dplyr, doBy, and ggplot2. The script has install.packages commands for these 3 packages. Even thought the packages are already installed it still downloads, builds, and installs them, which is very time consuming. Is there a way to have it only do the install if the package is not already installed? Also, I run in a docker container,

I have just uploaded the package "stable-0.1.tgz" to the contrib section of CRAN. It enables to compute the density ('dstable'), the distribution ('pstable'), the quantile ('qstable') and the hazard ('hstable') functions of a stable variate. 'stable.mode' computes the mode of a stable distribution. The procedure 'stableglm' also enables

I got some R code that I don't understand. Question as comment in code //where is t comming from, what is phi inverse rAC <- function(name, n, d, theta){ #generic function for Archimedean copula simulation illegalpar <- switch(name, clayton = (theta < 0), gumbel = (theta < 1), frank = (theta < 0), BB9 = ((theta[1] < 1) | (theta[2] < 0)), GIG = ((theta[2] < 0) |

Hi all: I have a question on sample size calculation of 2 groups of data. If 2 groups of data are all normal distribution, then I can use the function "n.indep.t.test.eq" from samplesize package.But if 2 groups of data are all skewed distribution, but not normal distribution,how can I calculate the sample size then? I've tried many transformation (e.g. log arcsin…) in order to

Hi all: I have a question about the sample size calculation. It's a pilot study,which includes 2 groups(low,high),3 time point(3,6,9 monthes).Each person has 3 results which according to the 3 time points.So it's a longitudinal study. I want to calculate the minimum sample size from the pilot study, but can't find the solution since the data is highly skewed and it's a

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Full_Name: Peter Fischer Hallin Version: Version 1.8.1 OS: Irix64 Submission from: (NULL) (130.225.67.236) I've made a script look like this: exp <- read.table("graph/1933672048.cluster.data") exp <- as.matrix(exp) postscript("graph/1933672048.cluster.data.ps") heatmap(exp,scale="none",cexCol=0.4,cexRow=0.2,col=custom,margins=c(5,5)) The row labels

All, Can someone help me create a skewed distribution, mean = 30, with probability of selecting a random number from the distribution greater than or equal 60 equal to 10%? I need the probability density function to equal zero at zero, and have a maximum height at or near 30. Is this possible? And if it is possible, how can I adjust the distribution so that the probability of selecting a

Dear R'ers, I would like to use barplot or a similar function to plot data demonstrating the distribution of the length of a kind of conservation in about 25000 DNA sequences. My data look like this: #Total sequences: 23873 0 19936 1 218 2 391 3 477 4 360 5 431 6 294 7 215 8 320 9 209 10 160 (.....) 99 0 100 1 101 0 102 0 103 1 104 0 105 0 106 0 107 0 108 0 109 1 Therefore, I would like

Last week I migrated some of our servers to Asterisk 1.4.18 and we started seeing audio drops of several seconds during SIP calls. After investigating it we noticed that Asterisk was increasing the RTP timestamps abnormally during a conversation. I'm including a text file with a subset of the data collected by Wireshark that shows the problem (I have the complete packet capture if anybody