similar to: Query on p-value

Dear Sir, I am using RClimDex. I get following error. Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, : scan() expected 'a real', got 'T' I have done copy paste of climate data from excel file to notepad and tried to upload. I do not have any knowledge about programming languages. Please help me. Regards, Binaya Pasakhala -- View this

Dear All, I have been using RClimdex for indices calculation. After completion of indices calculation, I get few statistical information on each output. Such as R2=3.4 p-value=0.333 Slope estimate= -7.774 and Slope error= 7.891 Now I would like to know, what do they mean and how shall I interpret them. Thank you. Regards. Binaya Pasakhala [[alternative HTML version deleted]]

Hi, I run the example for princomp for R211 I got the following error for biplot > ## The variances of the variables in the > ## USArrests data vary by orders of magnitude, so scaling is appropriate > (pc.cr <http://pc.cr> <- princomp(USArrests)) # inappropriate Erreur dans cov.wt(z) : 'x' must contain finite values only > princomp(USArrests, cor = TRUE) # =^=

Hi, My objective is to calculate "Relative (Cumulative) Frequency of Event Occurrence" - something as follows: Sample.Number 1st.Fly 2nd.Fly Did.E.occur? Relative.Cum.Frequency.of.E 1 G B No 0.000 2 B B Yes 0.500 3 B G No 0.333 4 G B No 0.250 5 G G Yes 0.400 6 G B No 0.333 7 B B Yes 0.429 8 G G Yes 0.500 9 G B No 0.444 10 B B Yes 0.500 Please refer to the code below:

I have a vector of size 217 called "A". the values of A are not sorted and range from 0 to 1 (normalized) I am having difficulty writing a program to create a new vector "B" where if A's value is 0< A <=0.333 then B is 0 if A's value is 0.333< A <=0.666 then B is 1 if A's value is 0.666< A <=1 then B is 2 so if A is 0.22 0.999 0.444 0 B would

> > Hi all, > I have a vector xm say: xm = c(1,2,3,4,5,5,5,6,6) > > I want to return a vector with the corresponding probabilities based on the > amount of times the numbers occurred. For example, I should get the > following vector for xm: > prob.xm = c(1/9, 1/9, 1/9, 1/9, 3/9, 3/9, 3/9, 2/9, 2/9) > Using prop.table gives: Usage (with table) > prob.xm <-

hello, i have been using ccf() to look at the correlation between lightning and electrogamnetic data. for the most part it has worked exactly as expected. however, i have come across something that puzzles me a bit: > x <- c(1, 0, 1, 0, 1, 0) > y <- c(0, 0, 0, 0, 0, 0) > ccf(x, x, plot = FALSE) Autocorrelations of series 'X', by lag -4 -3 -2 -1 0

Hello: I have a vector with 120,000 reals between 0.00000 and 0.9999 They are not sorted but the vector index is the time-order of my measurements, and therefore cannot be lost. How do I use R to find the starting and ending index of ANY and ALL the "series" or "sequences" in that vector where ever there are 5 or more members in a row between 0.021 and 0.029 ? For

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

Dear R-users, I have output files having a variable number of tables in the following format: ------------- 1 Pietje I1 I2 Value 1 1 0.11 1 2 0.12 2 1 0.21 2 Jantje I1 I2 I3 Value 1 1 1 0.111 3 3 3 0.333 ... ------------- Would there be an easy way of turning this into (a list of) data.frames with names Pietje, Jantje and variables I1,I2,...Value? (I1,I2 are string or categorical,

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474

Hello, I would like to be able to update an existing column in a dataframe, like this... data$score[data$type=="1" & data$year=="2001"]<-data$score * 0.111 data$score[data$type=="1" & data$year=="2002"]<-data$score * 0.222 data$score[data$type=="1" & data$year=="2003"]<-data$score * 0.333 ...but, if possible,

Hello all I would like to ask your help use mapply. I have a function called findCell that takes two arguments(x,sr) where x is a vector of size two (e.g x<-c(2,3) and sr is a matrix. I would like to call many times the findCell function (thus I need mapply) for different x inputs but always for the same sr. as x is a vector of size two (two cells) I want to pass inside inside the following

Hi, I was wondering if there is anything more efficient than split to do the kind of conversion in the subject. If I create a data frame as in system.time({fd = data.frame(x=1:2000, y = rnorm(2000), id = paste("x", 1:2000, sep =""))}) user system elapsed 0.004 0.000 0.004 and then I try to split it > system.time(split(fd, 1:nrow(fd))) user system elapsed

Hi.? There appears to be a bug in R function manova.? My friend and I both ran it the same way as shown below (his run) with the shown data set. His results are shown below. we both got the same results.? I was running with R 2.3.1. I'm not sure what version he used. Thanks very much, David Booth Kent State University -----Original Message----- From: dvdbooth at cs.com To: kberk at

Hello, I am trying to plot means and standard errors conditioned by a factor, using qplot. I am successful at getting the bar graph I want with a error bar, however I have tried many things and cannot get the bars to change colors. Currently showing as red and blue, but need it to be black and white for publication. Any suggestions please? Using a data set June, which is str:

I am hoping for some advice regarding limiting decimal points to 3. 'Round' produces the desired results except for the 97.5% confidence interval. Any advice as to how I modify the code to obtain output to 3 decimal points for all ouput is appreciated, regards Bob Green mod.multgran <-multinom(offence ~ grandiose * violent.convictions, data = kc, na.action = na.omit)

Hello there, I have two groups (men and women) and I know per group how many of them smoke or don't smoke (women 40 of 200; men 100 of 300). I would like to know how I can compare in R if men and women differ significantly in their smoking. However, because there are more men in the sample than women I cannot just compare the number of smokers and non-smokers in both groups, right?! (I would

Hi, I am using fanny and I have estrange results. I am wondering if someone out there can help me understand why this happens. First of all in most of my tries, it gives me a result in which each object has equal membership in all clusters. I have read that that means "the clustering is entirely fuzzy". Looking at the graphics it is really difficult to understand how objects with so

I've recently come across the following results reported from the lm() function when applied to a particular type of admittedly difficult data. When working with small data sets (for instance 3 points) with the same response for different predicting variable, the resulting slope estimate is a reasonable approximation of the expected 0.0, but the p-value of that slope estimate is a surprising