similar to: Probability of data values form DENSITY function

Hello,   What function can I use for matrices addition? I couldn’t find any information about it in the manual or in the internet. (A+B suits, when the number of matrixes is small, function sum() doesn’t suit for matrices addition, because it sums all variables in the matrices and produces as an answer single number, not a matrix).   Best regards, Lina [[alternative HTML version

Hello,   Could someone help me please and to tell how to get the probability from empirical distribution (not parametric) for each data value (R function). For example, for normal distribution there is such a function like:   “pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)”   I need the same function only for the empirical distribution (which does not correspond to any typical

Hello,   Could someone help me please and to tell how to get the probability from empirical distribution (not parametric) for each data value (R function). For example, for normal distribution there is such a function like:   “pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)”   I need the same function only for the empirical distribution (which does not correspond to any typical

Hi All , Could you please tell using which library ,Dickey-Fuller Test can be run? Thanks a lot __________________________________________________ [[alternative HTML version deleted]]

Dear WizaRds, dear Thomas, First of all, I want to tell you how grateful I am for all your support. I wish I will be able to help others along one day the same way you do. Thank you so much. I am struggling with a multistage sampling design: library(survey) multi3 <- data.frame(cluster=c(1,1,1,1 ,2,2,2, 3,3), id=c(1,2,3,4, 1,2,3, 1,2), nl=c(4,4,4,4, 3,3,3, 2,2), Nl=c(100,100,100,100,

Dear R users, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance with kruskal.test() function. I am comparing three different groups. The preliminary analysis using the kruskal-wallis-test show significance, but I still don''t know the relationship and the significance level

Dear Sirs, I would like to ask you, what function can I use for matrices addition? I couldn't find any information about it in the manual or in the internet. (A+B suits, when the number of matrixes is small, function sum() doesn't suit for matrices addition, because it sums all variables in the matrices and produces as an answer single number, not a matrix). I would be very thankful for

Short question: Is it possible to use statistical tests, like the Augmented Dickey-Fuller test, in functions with for-loops? If not, are there any alternative ways to scale measures? Detailed explanation: I am working with time-series, and I want to flag curves that are not stationary and which display pulses, trends, or level shifts. >df DATE ID VALUE2012-03-06 1

I'm having trouble creating a looping variable and i can't see wher ethe problem arises from any hep gratfully appreciated First create a table x<-table(SURVEY$n_0,exposed) > x exposed False True Under 16 24 1 16-19 68 9 20-24 190 37 25-34 555 204 35-44 330 87 45-54 198 65 55-64 67 35 65+

Hello R Help, I am trying solve an MLE convergence problem: I would like to estimate four parameters, p1, p2, mu1, mu2, which relate to the probabilities, P1, P2, P3, of a multinomial (trinomial) distribution. I am using the mle2() function and feeding it a time series dataset composed of four columns: time point, number of successes in category 1, number of successes in category 2, and

Hi, This is my first time posting to the mailing list, so if I'm doing something wrong, just let me know. I've taken ~1000 samples from 8 biological replicates, and I want to somehow combine the density functions of the replicates. Currently, I can plot the density function for each biological replicate, and I'd like to see how pool of replicates compares to a simulation I conducted

Hi, I am using oggz-chop in the ubuntu jaunty, am I doing something wrong? $ oggz-chop -o yt1.ogv -s0 -e500 ondrej.ogv Segmentation fault gdb session doesn't reveal much, since it isn't compiled with debugging symbols: (gdb) bt #0 0x00007f9e5d2f0092 in memcpy () from /lib/libc.so.6 #1 0x0000000000403698 in ?? () #2 0x000000000040262e in ?? () #3 0x000000000040285d in ?? () #4

Dear all, I have some trouble understanding the chisq.test function. Take the following example: set.seed(1) A <- cut(runif(100),c(0.0, 0.35, 0.50, 0.65, 1.00), labels=FALSE) B <- cut(runif(100),c(0.0, 0.25, 0.40, 0.75, 1.00), labels=FALSE) C <- cut(runif(100),c(0.0, 0.25, 0.50, 0.80, 1.00), labels=FALSE) x <- table(A,B) y <- table(A,C) When I calculate the test statistic by hand

Hello, How do I import data from Excel onto R? I am using S-Plus Envstat module. I need to use some of the data that already exist in the Envstat and put it into R to make graphs, find basic informations like mean, median, standard deviation, etc. I have been reading the help links, but I don't see anything in reference to this. Please help me! -Maher Lina

Dear list! I have run into a problem that seems very simple but I can't find any solution to it (have searched the internet, help-files and "An introduction to R" etc without any luck). The problem is the following: I would like to create a data.frame with two components (columns), the first component being a matrix and the second component a vector. Whatever I have tried so far, I

Hi R-users, I am using arima to fit a time series. Now I would like to include an intervention component "It (0 before intervention, 1 after)" using different types of impacts, that is, not only trying the simple abrupt permanent impact (yt = w It ) with the xreg option but also trying with a gradual permanent impact (yt= d * yt-1 + w * It ), following the filosophy of Box and Tiao

All, I realize from the archive that the sort argument in merge has been subject to discussion before, though I couldn't find an explanation for this behavior. I tried to simplify this to (kind of) minimal code from a real example to the following (and I have no doubts that there are smart people around achieving the same with smarter code :-)). I'm running R 2.15.1 64bit under MS Windows

Hi! Does anyone know how to do the test for goodness of fit of a logistic model (in rms package) after running fit.mult.impute? I am using the rms and Hmisc packages to do a multiple imputation followed by a logistic regression model using lrm. Everything works fine until I try to run the test for goodness of fit: residuals(type=c("gof")) One needs to specify y=T and x=T in the fit. But

Here are another three problems with logarithmic scales: 1) segments() does not work with logarithmic scales. I suggest to change lines 962-973 in "plot.c": for (i = 0; i < n; i++) { if (FINITE(xt(x0[i%nx0])) && FINITE(yt(y0[i%ny0])) && FINITE(xt(x1[i%nx1])) && FINITE(yt(y1[i%ny1]))) { GP->col = INTEGER(col)[i % ncol];

Dear R users, I still feel new to R so please apologize if I am doing something stupid here. My use of the polygon() function produces a result that I cannot comprehend: In a plot, I would like to shade the area below a normal distribution. However, I do not want the entire area to be shaded, but just the area on the right side of a vertical line that I draw through the distribution (in