Displaying 6 results from an estimated 6 matches for "allval".
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allvals
2006 Sep 23
1
Fitdistr() versus nls()
...me if there's a major mistake in the code?
Thanks in advance,
Luca
------ BEGINNING OF CODE
----------------------------------------------------------------
cdf.all=read.table("all_failures.cdf", header=FALSE, col.names=c
("ttr", "cdf"), sep=":" )
allvals.x=array(t(cdf.all[1]))
allvals.y=array(t(cdf.all[2]))
library(MASS)
bestval.exp.nls=bestval.exp.fit=-1
plot(allvals.x, allvals.y)
for(it in 1:100){
#extract random samples
random=sort(sample(1:length(allvals.x), 15))
somevals.x=allvals.x[c(random)]
somevals.y=allvals.y[c(random)]
#fit with n...
2002 Dec 04
1
Mixture of Multivariate Gaussian Sample Data
Hey, I am confused about how to generate the sample data from a mixture of
Multivariate Gaussian ditribution.
For example, there are 2 component Gaussian with prior
probability of 0.4 and 0.6,
the means and variances are
u1=[1 1]', Cov1=[1 0;0 1]
and
u2=[-1 -1]', Cov2=[1 0;0 1]
repectively.
So how can I generate a sample of 500 data from the above mixture
distribution?
Thanks.
Fred
2012 Nov 23
1
Student-t distributed random value generation within a confidence interval?
Dear R-users!
I?m faced with following problem:
Given is a sample where the sample size is 12, the sample mean is 30, and
standard deviation is 4.1.
Based on a Student-t distribution i?d like to simulate randomly 500 possible
mean values within a two-tailed 95% confidence interval.
Calculation of the lower and upper limit of the two-tailed confidence
interval is the easy part.
m <- 30 #sample
2009 May 22
0
EM algorithm mixture of multivariate
...le
#########################
#Start Script
#########################
library(mvtnorm)
libray(scatterplot3d)
library(MASS)
n=100
m1=c(5,-5)
m2=c(-3,3)
s1=matrix(c(2,1,1,3), 2,2)
s2=matrix(c(4,1,1,6), 2,2)
alpha=0.3
c1 <- mvrnorm(round(n*alpha),m1,s1)
c2 <- mvrnorm(round(n*(1-alpha)),m2,s2)
allval <- rbind(c1,c2)
x <- allval[sample(n,n),]
mixm<-
function(x,m1,m2,s1,s2, alpha)
{
f1<-dmvnorm(x, m1, s1, log=FALSE)
f2<-dmvnorm(x, m2, s2, log=FALSE)
f=alpha*f1+(1-alpha)*f2
f
}
plot(x)
den<-mixm(x,m1,m2,s1,s2,alpha)
scatterplot3d(x[,1],x[,2],den, highlight.3d=TRUE...
2009 May 22
0
EM algorithm mixture of multivariate gaussian
...le
#########################
#Start Script
#########################
library(mvtnorm)
libray(scatterplot3d)
library(MASS)
n=100
m1=c(5,-5)
m2=c(-3,3)
s1=matrix(c(2,1,1,3), 2,2)
s2=matrix(c(4,1,1,6), 2,2)
alpha=0.3
c1 <- mvrnorm(round(n*alpha),m1,s1)
c2 <- mvrnorm(round(n*(1-alpha)),m2,s2)
allval <- rbind(c1,c2)
x <- allval[sample(n,n),]
mixm<-
function(x,m1,m2,s1,s2, alpha)
{
f1<-dmvnorm(x, m1, s1, log=FALSE)
f2<-dmvnorm(x, m2, s2, log=FALSE)
f=alpha*f1+(1-alpha)*f2
f
}
plot(x)
den<-mixm(x,m1,m2,s1,s2,alpha)
scatterplot3d(x[,1],x[,2],den, highlight.3d=TRUE...
2011 Apr 09
1
loop and sapply problem, help need
Dear R experts
Sorry for this question
M1 <- 1:10
lcd1 <- c(11, 22, 33, 44, 11, 22, 33, 33, 22, 11)
lcd2 <- c(22, 11, 44, 11, 33, 11, 22, 22, 11, 22)
lcd3 <- c(12, 12, 34, 14, 13, 12, 23, 23, 12, 12)
#generating variables through sampling
pvec <- c("PR1", "PR2", "PR3", "PR4", "PR5", "PR6", "PR7",