search for: laguerr

...igma) * dnorm(x, observed, sigma) Then, given the parameters: mu <- 300 sigma <- 50 m <- 250 target <- 200 sigma_i <- 50 I can use the function integrate as: > integrate(ff, lower= -Inf, upper=target) 0.002169851 with absolute error < 4.4e-05 I would like to also use Gauss-Laguerre methods to also integrate this function. In doing so, I believe the only change of variable needed when integrating from -Inf to target is x = target - y_i where y_i is node i. As such, I can implement the following: library(statmod) falsePos <- function(target, m, mu, sigma, sigma_i, Q = 30)...

...e estimated from another procedure. But, for sake of argument assume N(0,1). My challenge was to get the appropriate nodes and weights for the numerator since I am going from -Inf to c. So, what I did to get this to work was get the quadrature nodes and weights using > gauss.quad(49,kind="laguerre") Then, I do the following to get them to work with a normal distribution: F(y) = p(y+c) * N(y+c|\mu, \sigma^2) Where y is the laguerre node and c is the lower bound of integration. Subsequently, I plug this into the following \sum_{i=1}^Q F(y_i)e^y_i \cdot w_i Where i indexes node and w...

...o evaluate an integral from -inf to a etc. I've read through the help and searched the archives and didn't see any relevant discussion on whether it is possible to use this function to get the weights for -inf to a. Only two hits come up in the archive and neither was relevant. I think the Laguerre quadrature in gauss.prob might be the right path, but I'm uncertain. Is it possible to get the nodes and weights I need from R directly, or should I refer to a table that has derived these for the normal distribution from another source? thank you Harold > gauss.quad.prob(10, dist=...

Hi all, We know that Hermite polynomial is for Gaussian, Laguerre polynomial for Exponential distribution, Legendre polynomial for uniform distribution, Jacobi polynomial for Beta distribution. Does anyone know which kind of polynomial deals with the log-normal, Student抯 t, Inverse gamma and Fisher抯 F distribution? Thank you in advance! David [[alternative H...

...ke.mat } # turn this off for now #like.mat <- function(score, items, theta){ #matrix(mapply(pcm,rep(theta,length(items)),items,score),ncol=length(the ta),byrow=TRUE) #} class.numer <- function(score,items, prof_cut, mu=0, sigma=1, aboveQ){ gauss_numer <- gauss.quad(49,kind="laguerre") if(aboveQ==FALSE){ mat <- rbind(like.mat(score,items, (prof_cut-gauss_numer$nodes)), dnorm(prof_cut-gauss_numer$nodes, mean=mu, sd=sigma)) } else { mat <- rbind(like.mat(score,items, (gauss_numer$nodes+prof_cut)), dnorm(gauss_numer$nodes+prof_cut, mean=mu,...