similar to: "normal probability plot" with a percentile scale?

Hi all, I am a freshman of R,but I am interested in it! Those days,I am learning pages on NIST,with url http://www.itl.nist.gov/div898/handbook/eda/section3/probplot.htm, I am meeting a problem about probability plot and I don't know how to plot a data set with R. Could somebody tell me the answer,and a example is the best! I will look forward to your answer. Thank you very much.

Hola a todos: Estoy intentado realizar un modelo senoidal de unos datos de radiación solar con el fin de afrontar el relleno de la serie y aplicar la prueba de Thom para verificar su homogeneidad [0]. De momento me encuentro con los siguientes problemas: 1- ¿Existe la prueba de Thom en R? ¿O debo crearme mi propia función? 2- Para la realización del modelo senoidal estoy siguiendo los pasos

Dear R-Users, How can I use chisq.test() as a goodness of fit test? Reading man-page I?ve some doubts that kind of test is available with this statement. Am I wrong? X2=sum((O-E)^2)/E) O=empirical frequencies E=expected freq. calculated with the model (such as normal distribution) See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm for X2 used as a goodness of fit test. Any

Does anyone have code to plot bihistograms in R? See http://www.itl.nist.gov/div898/handbook/eda/section3/bihistog.htm for a description of a bihistogram. -- Hal Varian voice: 510-643-4757 SIMS, 102 South Hall fax: 510-642-5814 University of California hal at sims.berkeley.edu Berkeley, CA 94720-4600 http://www.sims.berkeley.edu/~hal

Hello all, Would somebody be kind enough to show me how to do a KS test in R for a lognormal distribution with ESTIMATED parameters. The R function ks.test()says "the parameters specified must be prespecified and not estimated from the data" Is there a way to correct this when one uses estimated data? Regards, Kwabena. -------------------------------------------- Kwabena Adusei-Poku

Hi, Can anyone please provide the formula used to compute ACF(nlme). I believe the one that is used in R is of the type mentioned on the website. Please correct me if I am wrong. The normalization of the numerator (Ch) has been done by 'N' where as I would like to do it by 'N-k'. Is there anyway in the present implementation of ACF to normalize it by 'N-k', where

Hi, from what you're writing: "The logaritmic transformation "shapiro.test(log10(y))" says: W=0.9773, p-value= 2.512e-05." it seems the log-values are not distributed normally and so original data are not distributed like a log-normal: the p-value is extremally small! Other tests for normality are available in package: nortest compare the log-transformation of your ecdf

hi! I would like to ask help how to generate numbers from g-and-h distribution. This distribution is like normal distribution but span more of the kurtosis and skewness plane. Has R any package on how to generate them? Any help will be greatly appreciated. Thank you so much! Form, Filame Uyaco --------------------------------- [[alternative HTML version deleted]]

Hi, pchisq -> distribution function dchisq -> density function pval is the area under the curve, to calculte it you use distribution function which is the integral of density function. See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda362.htm http://mathworld.wolfram.com/DistributionFunction.html f(x) density function F(x) distribution function =Pr(X<x)= integral(f(x))

I have run a t.test in R, and received these results: Two Sample t-test data: rsa and umple t = 0.9819, df = 10, p-value = 0.3493 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -76.1541 196.1541 sample estimates: mean of x mean of y 508.3333 448.3333 Can someone give me a detailed interpretation of the above results? Specifically,

R plotting experts: I have a bivariate dataset composed of 300 (x,y) continuous datapoints. 297 of these points are located within the y range of [0,10], while 2 are located at 20 and one at 55. No coding errors, real outliers. When plotting these data with a scatterplot, I obviously have a problem. If I plot the full dataset with ylim = c(0,55), then I cannot see the structure in the data in

Hi, Is there a function that does percentile-percentile plot. I do not mean the qqplot. I need to plot the percentiles rather than points themselves. I am hoping for a plot that tells me that the x percentile of one data set corresponds to the y percentile of the other. for example a point on the plot of (.5, .2) will tell me that the 50th percentile of the first data and the 20th percentile of

Hi, all dear R experts, I am really stuck by how to get the 5th percentile( with a 95% CI )of the Kaplan-meier estimator of survival function P(T>t). I have a simulated sample of lifetime Ts, then I set the KM estimator < km.fit<-survfit(Surv(T),type="kaplan-meier",data=Surv(T)) <quantile(km.fit,.05) However, it gave "Error in order...". Does someone have some

Hi- I wanted percentage labels on a qqnorm x axis. I used the following: #make up some data jt<-rnorm(100) #qqnorm with percentile x labels qqnorm(jt,axes=F,xlab="Percentiles") box() l<-c(1,5,10,30,50,70,90,95,99) axis(1,at=qnorm(l/100),label=l) which was ok for this data set. Does anyone have a more general solution which would allow one to specify the number of x labels

Hi, How do I get R to output the 95% cutoff from a distribution of a continous variable? summary() only displays a few statistics.... Thanks!

hello; firstly, my gratitude to all who help me to find a function that allows me to add confidence interval to my graph. in order to calculate the (1-alpha)th percentile of for exemple an F(df1,df2) distribution i do like this: v<-df(alpha,df1,df2) percentile<-qf(v,df1,df2,alpha) if it is true please alert me , and if it is not what should do then? :handshake: -- View this message in

Has anyone developed a defensible method of estimating percentiles from a univariate kernel density estimate? I am working on a problem in which the density estimate is of interest, but I would also like to estimate the value of the variable for which the distribution was, say, 0.20. I spent some time searching the archives and found some message from 2006 that implied such a method was not

Hello all, Thanks in advance for you attention. I would like to generate a third value that represents the quantile value of a variable in a data frame. # generating data x <- as.matrix(seq(1:30)) y <- as.matrix(rnorm(30, 20, 7)) tmp1 <- cbind(x,y) dat <- as.data.frame(tmp1) colnames(dat) <- c("id", "score") dat # finding percentiles of "score"

Heeeelp Given this data x <- c(1,5,100,300,250,200,550,900,1000) > quantile(x) 0% 25% 50% 75% 100% 1 100 250 550 1000 When I run the quantile, I can only know the value of the nth percentile I want to know what's the percentile position of each items in the list Sample 1 = 100% on the list has 1 or more 5 = more than x% on the list has 5 or more 100 = more than x% on the

In R, what is the best way to convert z-scores (Normal distribution) to a percentiles, and vice-versa. (I'll be looking to do the same with other distributions eventually.) === Peter Petto <ppetto at ppetto.com> Bay Village, OH 440.249.4289