similar to: plotting the ending point in a for loop

I would like to plot multiple random walks onto the same graph. My p variable dictates how may random walks there will be. par(mfrow=c(1,1)) p <- 100 N <- 1000 S0 <- 10 mu <- 0.03 sigma <- 0.2 nu <- mu-sigma^2/2 x <- matrix(rep(0,(N+1)*p),nrow=(N+1)) y <- matrix(rep(0,(N+1)*p),nrow=(N+1)) t<- (c(0:N))/N for (j in 1:p) { z <- rnorm(N,0,1) x[1,j] <- 0 y[1,j]

Hi, I have been using maxLik to do some MLE of Geometric Brownian Motion Process and everything has been going fine, but know I have tried to do it with jumps. I have create a vector of jumps and then added this into my log-likelihood equation, know I am getting a message: NA in the initial gradient My codes is hear # n<-length(combinedlr) j<-c(1,2,3,4,5,6,7,8,9,10)

Here's another example of my plotmath whipping boy, the Normal distribution. A colleague asks for a Normal plotted above a series of axes that represent various other distributions (T, etc). I want to use vectors of equations in plotmath to do this, but have run into trouble. Now I've isolated the problem down to a relatively small piece of working example code (below). If you would

Hello all, I have what I think is a simple question but I've been unable to solve it. I have the following string: A[&states=1]:[&rate=2]425, B[&states=3]:[&rate=5]500 I would like to combine the two expressions in the [], so that only one set of [] is present after each letter, so that I have the following string: A:[&states=1,&rate=2]425,

Dear Rusers, I have used R,S-PLUS and SAS to analyze the sample data "bacteria" in MASS package. Their results are listed below. I have three questions, anybody can give me possible answers? Q1:From the results, we see that R get 'NAs'for AIC,BIC and logLik, while S-PLUS8.0 gave the exact values for them. Why? I had thought that R should give the same results as SPLUS here.

Dear all, I have what is a bit of a confusing question, so I hope that I can explain clearly. Thank you for your help in advance. I would like to do a replacement procedure on several strings, but the way that I am currently going about it is not working. I have defined "len", which is a series comprising the lengths of different items, all preceded by a colon. > len [1]

Dear all, I want to use the deltavar() function from emdbook. I can use it directly from the command terminal but within a function it behaves weird. Working example: ---------------------- library("emdbook") fn <- function() { browser() y <- 2 print(deltavar(y*b2, meanval=c(b2=3), Sigma=1) ) } x <- 2 print(deltavar(x*b1, meanval=c(b1=3), Sigma=1) ) y<-3 fn()

I've two data.tables as shown below: *** N = 10 A.DT <- data.table(a1 = c(rnorm(N,0,1)), a2 = NA)) B.DT <- data.table(b1 = c(rnorm(N,0,1)), b2 = 1:N) setkey(A.DT,a1) setkey(B.DT,b1) *** I tried to change my previous data.frame implementation to a data.table implementation by changing the for-loop as shown below: *** for (i in 1:nrow(B.DT)) { for (j in nrow(A.DT):1) { if

Hi, I'm a new user of R. My background is Electrical Engineering, so please bear with me if this is a silly question. I'm trying to assess whether the results of an experiment satisfy the hypothesis of homoscedasticity (my ultimate goal is to use ANOVA). The result of the experiment is mean delay (dT), which depends on three factors, topology, drift, and lambda. The first two factors are

On May 19, 2009, at 8:15 PM, Nick Lewycky wrote: > Eli Friedman wrote: >> On Tue, May 19, 2009 at 12:30 PM, Nicolas Geoffray >> <nicolas.geoffray at lip6.fr> wrote: >>>> The pi functions can be implemented with copy instructions. >>> Store instructions? >> >> I would assume something more like "select i1 true, <ty> %val, <ty>

Hi All, I met a problem using readLines function to return the data from Google maps. readLines(url(" http://ditu.google.cn/maps/geo?q=+qianshuichong,+guichi+anhui,+CN&output=csv&key=ABQIAAAAq8Fnd_oUka-7RdS6BrD7GBTqeABoQuNTXS36G_rkiwQnKRW6GBTkns8JpKz6y6dScgB8827dlddUlg"), n=1, warn=FALSE) [1] "200,4,30.6528380,117.4872250" The above code is ok because the

Hi I use gnls to fit non linear models of the form y = alpha * x**beta (alpha and beta being linear functions of a 2nd regressor z i.e. alpha=a1+a2*z and beta=b1+b2*z) with variance function varPower(fitted(.)) which sounds correct for the data set I use. My purpose is to use the fitted models for predictions with other sets of regressors x, z than those used in fitting. I therefore need to

Hi, my data set is data.frame(id, yr, y, l, e, k). I would like to estimate Lee and Schmidts (1993, OUP) model in R. My colleague wrote SAS code as follows: ** procedures for creating dummy variables are omitted ** ** di# and dt# are dummy variables for industry and time ** data a2; merge a1 a2 a; by id yr; proc sysnlin maxit=100 outest=beta2; endogenous y; exogenous l e k

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Hi, I have had some troubles using doubleYScale. No matter what I try, I cant manage to change the color of the y-axis in the end. I have to produce a black and white plot. There is also something I do not understand regarding fontfamilyj="serif" when using it in: strip=strip.custom() Maybe someone has a better idea for defining which line and dots belong to which y-axis when not using

Dear all, is there anyone who can help me extracting p-values from an Anova object from the car library? I can't seem to locate the p-values using str(result) or str(summary(result)) in the example below > A <- factor( rep(1:2,each=3) ) > B <- factor( rep(1:3,times=2) ) > idata <- data.frame(A,B) > fit <- lm( cbind(a1_b1,a1_b2,a1_b3,a2_b1,a2_b2,a2_b3) ? sex,

Hi folks, Suppose I create the character vector charvec by > charvec<-c("a1.b1","a2.b2") > charvec [1] "a1.b1" "a2.b2" and then I use strsplit on charvec as follows: > splitlist<-strsplit(charvec,split=".",fixed=TRUE) > splitlist [[1]] [1] "a1" "b1" [[2]] [1] "a2" "b2" I was wondering

Hi I searched in the list and only found questions without answers e.g. http://finzi.psych.upenn.edu/R/Rhelp02a/archive/19955.html : Is there a way to get the same results with lme as with aov with Error()? Can anybody reproduce the following results with lme: id<-c(1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,1,1,1,2,2,2,3,3,3,4,4,4,5,5,5)

Dear Wiz[R]ds, I am deeply grateful for the help from Duncan Murdoch, Gray Calhoun, and others. We are almost there. For whatever reason, I can't change the symbol from a circle to a triangle in the upright posture plots. Any ideas? I have included the problem in full. # tritiated (3H)-Norepinephrine(NE) disappearance from plasma # concentrations supine and upright # supine datasu <-

Hello all... I am just starting to teach myself Bayesian methods, and am interested in learning how to use UMacs. I've read the documentation, but the single example is a bit over my head at the level I am at right now. I was wondering if anyone has any simple examples they'd like to share. I've successfully done a couple of simple gibbs examples, but have had a hard time