similar to: lower.tail option in pnorm

I am trying to fit a nonlinear model using nlm(). My application of nlm() is a bit complicated. Here is the story behind the model being fit: The observer is trying to detect a signal corrupted by noise. On each trial, the observer gets stim=signal+rnorm(). In the simulation below I have 500 trials. Each row of stim is a new trial. On each trial, if the cross-correlation between the stim and the

Hi, I'm trying to redefine the contrasts for a linear model. With a 2 level factor, x, with levels A and B, a two level factor outputs A and B - A from an lm fit, say lm(y ~ x). I would like to set the contrasts so that the coefficients output are -0.5 (A + B) and B - A, but I can't get the sign correct for the first coefficient (Intercept). Here is a toy example, set.seed(12161952) y

1)I am wandering how the following SQL statement can be written in R language w/o using sqldf: create table detail2 as select a.* from detail a, pdetail b where a.TDATE=b.TDATE and (a.STIM >= b.STIM and a.STIM <=b.MAXTIM) 2) when try if then in R it only applies to the 1st row & not to whole dataset like in SAS. How do you get round that? in SAS: data summary; set all1;

Dear all, I am having quite a hard time in trying to figure out how to correctly spell out a model in R (a repeated-measures anova with a within-subject covariate, I guess). Even though I have read in the posting guide that statistical advice may or may not get an answer on this list, I decided to try it anyway, hoping not to incur in somebody's ire for misusing the tool. For the sake of

Hi I'm reading a CSV file using read.table, and it keeps importing a text variable as a factor. To overcome this, I've used the as.is command referring to the variable in question (called "stim") data<-read.table(file.choose(), header=T, sep=",", as.is = "stim") However, "stim" is still imported as a factor. I notice there are other read.table

Hello all, I have a question about basic statistics. Given a PDF value of 0.328161, how can I find out the value of -0.625 in R? It is like reversing the dnorm function but I do not know how to do it in R. > pdf.xb <- dnorm(-0.625) > pdf.xb [1] 0.328161 > qnorm(pdf.xb) [1] -0.444997 > pnorm(pdf.xb) [1] 0.628605 Many thanks, Edwin -- View this message in context:

Hi, I'm trying to calculate the value of the variable, dp, below, in the argument to the integral of dnorm(x-dp) * pnorm(x)^(m-1). This corresponds to the estimate of the sensitivity of an observer in an m-alternative forced choice experiment, given the probability of a correct response, Pc, a Gaussian assumption for the noise and no bias. The function that I wrote below gives me an error:

Hello, First time poster here so let me know if you need any more information. I am trying to run an ordered probit with maximum likelihood model in R with a very simple model (model <- econ3 ~ partyid). Everything looks ok until i try to run the optim() command and that's when I get " Error in rep(1, nrow(x)) : invalid 'times' argument". I had to adapt the code from a 4

Hi I'm an R newbie. I can't seem to add new variables to data frames. Here are the stages (1) I import the data using read.csv. (2) I fix it using fix(data) (3) I create a new variable using spos<-tagPOS(stim,language="en",model=NULL,tagdict=NULL). (tagPOS is a function in the OpenNLP toolkit, which tags a string for part of speech. "stim" is a variable in the

grDevices::convertColor has arguments 'from' and 'to' which can take on value 'XYZ'. Can someone confirm that 'XYZ' is the same as the CIE chromaticity coordinates that are also sometimes refered to as 'xyY' in the literature? Or are these the CIE tristimulus values? It looks to me like the first case is true, but I would appreciate hearing from one of

Has anyone plotted or is it possible to plot CIE *xy* chromaticity diagram http://en.wikipedia.org/wiki/File:CIE1931xy_blank.svg I need this plot in color. ishida [[alternative HTML version deleted]]

Hello, I have a matrix (class matrix) composed of GridCell (row and column). The matrix value is the beta diversity index value between two grids. Now I would like to get the average value of each GridCell. Please kindly advise how to make the calculation. Thank you. Elaine The matrix looks like (cited from Michael Friendly) I would like to get the average value of each color. Obs

Dear all, I am estimating a mixed-model in Ubuntu Raring (13.04¸ amd64), with the code: fm0 <- lme(rt ~ run + group * stim * cond, random=list( subj=pdSymm(~ 1 + run), subj=pdSymm(~ 0 + stim)), data=mydat1) When I check the approximate variance-covariance matrix, I get: > fm0$apVar [1] "Non-positive definite

Hello, I've a question concerning the display of interval data. A sample dataset where X is an interval between Xa and Xb which should be displayed: Y=c(15,14,23,18,19,9,19,13) Xa=c(17,22,21,18,19,25,8,19) Xb=c(22,22,29,34,19,26,17,22) X = (Xa+Xb)/2 It's easily possible to plot the mean of the interval like: plot(X,Y) afterwards I can create lines for the interval with:

All, I am using a sum of squared differences in the objective function of an optimization problem I am doing and I have managed to speed it up using the outer function versus the nested for loops, but my suspicion is that the calculation could be done even quicker. Please see the code below for a simple example. If anyone can point out a faster way I would appreciate it greatly. Thanks, Roger

hi all, i got flooded by these msgs like 1000+ lines, any idea? my kernel is dated Nov-30 FreeBSD 4.9-stable # tail -f /var/log/messages Jan 18 19:43:23 xb /kernel: arp: 202.79.180.1 moved from 00:04:5a:49:eb:74 to 00:50:0f:4f:c0:00 on rl0 Jan 18 19:45:06 xb /kernel: arp: 202.79.180.1 moved from 00:50:0f:4f:c0:00 to 00:04:5a:49:eb:74 on rl0 Jan 18 19:45:18 xb /kernel: arp: 202.79.180.1 moved from

I have two lists: xa <- list( X=c(1,2,3), Y=c(4,5,6), Z=c(7,8,9) ) xb <- with( barley, tapply( X=seq(1:nrow(barley)), INDEX=site , FUN=function(z)yield[z])) I can convert xa to a dataframe easily with: as.data.frame(xa) But if i try the same with xb I get: as.data.frame(xb) Error in as.data.frame.default(xb) : can't coerce array into a data.frame What

Dear all Is there a simpler method to achieve the following: When I obtain an empty data.frame after subsetting, I need for it to contain one line of NAs. Here's a dummy example: > (.xb <- iris[ iris$Species=='zz', ]) [1] Sepal.Length Sepal.Width Petal.Length Petal.Width Species <0 rows> (or 0-length row.names) > dim(.xb) [1] 0 5 > (.xa <-

This patch adds support to find next 1 or 0 bit in a xbmitmap range and clear a range of bits. More possible optimizations to add in the future: 1) xb_set_bit_range: set a range of bits. 2) when searching a bit, if the bit is not found in the slot, move on to the next slot directly. 3) add tags to help searching. Signed-off-by: Wei Wang <wei.w.wang at intel.com> Cc: Matthew Wilcox

This patch adds support to find next 1 or 0 bit in a xbmitmap range and clear a range of bits. More possible optimizations to add in the future: 1) xb_set_bit_range: set a range of bits. 2) when searching a bit, if the bit is not found in the slot, move on to the next slot directly. 3) add tags to help searching. Signed-off-by: Wei Wang <wei.w.wang at intel.com> Cc: Matthew Wilcox