similar to: Get an expected value for Order Statistics by applying double integrals

Classification: UNCLASSIFIED Caveats: NONE Thanks for your quick response. The program you mentioned below available from R is based on number of runs (up or down) not based on a longest length of runs of same events. To be more specific, for example, from a series, HHTHTTTTHHH, the number of runs are 5, and the longest length of runs of the same events is 4. I'll check for the website you

Hello, R users, I am a very beginner of R and tried read.csv to import an excel file after saving an excel file as csv. But it added alternating rows of fictitious NA values after row number 16. When I applied read.delim, there were trailing several commas at the end of each row after row number 16 instead of NA values. Appreciate your help. Kyong [[alternative HTML version deleted]]

Classification: UNCLASSIFIED Caveats: NONE Dear R users, How can I retrieve an evaluated gradient value from "deriv" function provided below? I want to retrieve b0 value. Appreciate your help. Kyong junk1<-deriv(~(1/b1)*k-b0/b1,"b0",c("k","b0","b1"),formal=T) junk1(k=0,b0=-14.0236,b1=2.44031) [1] 5.746647 attr(, "gradient"):

Classification: UNCLASSIFIED Caveats: NONE Hello, R users, Has anybody written a function for random test based on the length of longest run of same events. I really appreciate your help. Kyong Park Classification: UNCLASSIFIED Caveats: NONE [[alternative HTML version deleted]]

Classification: UNCLASSIFIED Caveats: NONE Dear R users, I'm interested in finding a random effect of the Block in the data shown below, but 'lme' does not work without the random effect. I'm not sure how to group the data without continuous value which is shown in the error message at the bottom line. If I use 'aov' with Error(Block), is there a test method comparing

Hi, I would like to solve a double integral of the form \int_0^1 \int_0^1 x*y dx dy using Gauss Quadrature. I know that I can use R's integrate function to calculate it: integrate(function(y) { sapply(y, function(y) { integrate(function(x) x*y, 0, 1)$value }) }, 0, 1) but I would like to use Gauss Quadrature to do it. I have written the following code (using R's statmod package)

Dear R users, I'm using R 2.1.0 with Windows 2000. In the middle of a R session, an error message pops up saying Rgui.exe generated errors and shuts down the R session. How can I correct this problem? Appreciate your help. Kyong [[alternative HTML version deleted]]

Dear R useRs, i have the function f1(x, y, z) which i want to integrate for x and y. On the one hand i do this by first integrating for x and then for y, on the other hand i do this the other way round and i wondering why i doesn't get the same result each way? z <- c(80, 20, 40, 30) "f1" <- function(x, y, z) {dgamma(cumsum(z)[-length(z)], shape=x, rate=y)}

Hi all, I need to solve double integrals with no closed solution. Calling x and y the two variables we have x ~ Normal(y*v,1) and y ~Half-Normal(0,1). In fact, given a joint funcion g(x,y), I need evaluate the integral of this function under that random structure. Could anyone suggest me a package or even a suitable method to solve this problem? Thanks all, Caio

I have an R function defined as: f<-function(x){ return(dchisq(x,9,77)*((13.5/x)^5)*exp(-13.5/x)) } Numerically integrating this function, I observed a couple of things: A) Integrating the function f over the entire positive real line gives an error: > integrate(f,0,Inf) Error in integrate(f, 0, Inf) : the integral is probably divergent B) Increasing the interval of integration

I am trying to solve an integral in R. However, I am getting an error when I am trying to solve for that integral. The equation that I am trying to solve is as follows: $$ C_m = \frac{{abs{x}}e^{2x}}{\pi^{1/2}}\int_0^t t^{-3/2}e^{-x^2/t-t}dt $$ [image: enter image description here] The code that I am using is as follows: a <- seq(from=-10, by=0.5,length=100) ## Create a function to compute

Hi R users, I have a couple of questions about some problems that I am facing with regard to numerical integration and optimization of likelihood functions. Let me provide a little background information: I am trying to do maximum likelihood estimation of an econometric model that I have developed recently. I estimate the parameters of the model using the monthly US unemployment rate series

Hi all, I have some some problem with regard to finding the integral of a function containing an indicator function. please see the code below: func1 <- function(x, mu){ (mu^2)*dnorm(x, mean = mu, sd = 1)*dgamma(x, shape=2)} m1star <- function(x){ integrate(func1, lower = 0, upper = Inf,x)$val} T <- function(x){ 0.3*dnorm(x)/(0.3*dnorm(x)+0.7*m1star(x))} func2 <-

Hello, Could somebody point me, is there any function in R which returns expected values of order statistics for normal distribution? I have been looking and couldn't find it. Thanks! Anna

Hello all, I am trying to minimize a function which contains a double integral, using "nlminb" for the minimization and "adapt" for the integral. The integral is over two variables (thita and radiusb) and the 3 free parameters I want to derive from the minimization are counts0, index and radius_eff. I have used both tasks in the past successfully but this is the first time

Classification: UNCLASSIFIED Caveats: NONE R users, This is a summary for the responses I got from Sandra Dorai-Raj and Simon Blomberg followed by my question. Sandra suggested using lm instead of lme for a model without a random effect, and Simon suggested anova.lme instead of anova.lm for comparing two models with and without a random effect. For the anova test, both anova.lme and anova

Dear r-users, Is there any command in R allowing to evaluate a double integral? for instance let say I want to evaluate the following integral: integrate[lo=(0,1),up=(2,3)] f(x,y)=x^2+y^2 where lo is the vector of lower bounds and up that of upper bounds. I thaught the function "adapt" would work but it did not. Many thanks, Dominique K.

In the help for ?integrate: >When integrating over infinite intervals do so explicitly, rather than just using a large number as the endpoint. This increases the chance of a correct answer ? any function whose integral over an infinite interval is finite must be near zero for most of that interval. I understand that and there are examples such as: ## a slowly-convergent integral integrand

Sir, I want to calculate double integral in R. Is there any function to do this? Regards, Suman Dhara [[alternative HTML version deleted]]

Hi folks, I am having a question about efficiently finding the integrals of a list of functions. To be specific, here is a simple example showing my question. Suppose we have a function f defined by f<-function(x,y,z) c(x,y^2,z^3) Thus, f is actually corresponding to three uni-dimensional functions f_1(x)=x, f_2(y)=y^2 and f_3(z)=z^3. What I am looking for are the integrals of these three