Displaying 14 results from an estimated 14 matches for "prob1".
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2008 Apr 22
2
Multidimensional contingency tables
How does one ideally handle and display multidimenstional contingency
tables in R v. 2.6.2?
E.g.:
> prob1<- data.frame(victim=c(rep('white',4),rep('black',4)),
+ perp=c(rep('white',2),rep('black',2),rep('white',2),rep('black',2)),
+ death=rep(c('yes','no'),4), count=c(19,132,11,52,0,9,6,97))
> prob1
victim perp death count
1...
2010 Sep 06
1
calculating area between plot lines
Hi everyone. I have these data:
probClass<-seq(0,0.9,0.1)
prob1<-c(0.0070,0.0911,0.1973,0.2949,0.3936,0.5030,0.5985,0.6869,0.7820,0.8822)
prob2<-c(0.0066,0.0791,0.2358,0.3478,0.3714,0.3860,0.6667,0.6400,0.7000,1.0000)
# which I'm plotting as follows:
plot(probClass,prob1,xlim=c(0,1),ylim=c(0,1),xaxs='i',yaxs='i',type="n")
l...
2011 Oct 06
1
sum of functions
...er to maximize the log-likelihood
function, I have to sum these log-likelihood functions for each i and so to
get another function that is a function only of betas and so to maximize it
through maxLik for instance. Is that possible?
In order to be more clear I give an example of how it could be:
Prob1 <- function(b, i)
g.yj(b,y=1,h.np,i)/(g.yj(b,y=1,h.np,i)+g.yj(b,y=0,h.np,i))
loglik.i<- function(b, i) Y[i,]*log(Prob1(b,i))+(1-Y[i,])*log(1-Prob1(b,i))
where b denotes the betas, i the observations, Y is the response vector and
g.yj(b,1,h.np,i) a function that I created previously, Prob1(b...
2010 Mar 06
1
Plotting Comparisons with Missing Data
...got a data table that I've read from
a file containing some simple information about the performance of 4
algorithms. The columns are the name of the algorithm, the problem instance
and the resulting score on that problem (if it wasn't solved I mark that
with NA).
solver instance result
A prob1 40
B prob1 NA
C prob1 39
D prob1 35
A prob2 100
B prob2 50
C prob2 NA
D prob2 NA
A prob3 75
B prob3 80
C prob3 60
D prob3 70
A prob4 80
B prob4 NA
C prob4 85
D prob4 75
I've managed to read in the data as follows:
data <- table.read("./test.txt", header = TRUE, colClasses =
c(&quo...
2007 Jan 19
1
naive bayes help
...# number of training points
n.test <- 200 # number of test points
p<-2 # dimension of input space
z <- matrix(rnorm((n+n.test)*p),ncol=p)
x <- matrix(0,nrow=n+n.test,ncol=p)
for (i in 1:p)
x[,i] <- z%*%rnorm(p)
truecoef <- c(1,2)
prob1 <- exp(x%*%truecoef)/(1+exp(x%*%truecoef))
# prob is the true probability of class 1
y <- rbinom(n+n.test,1,prob1)
# separate the data into train and test sets
mydata <- data.frame(y=y[1:n],x=x[1:n,])
mydata.test <- data.frame(y=y[n+(1:n.test)],x=x[n+(1: n.test),])
#####################...
2000 Apr 05
2
My first R-program
Sorry, I pasted the wrong file in earlier... this is the correct one:
pValCalculator(b, n=20, m=20)
{
ind <- 1:min(c(n,m))
prob <- (1-pnorm(b,sd=std*sqrt(ind)))
prob1 <- sum((n-ind+1)*(m-ind+1)*prob)
prob1
}
inputData <-
scan("/users/lvssso/projects/LAMA/output/pValLamaScore.tmp", list(block1
= "",block2 = "",width1 = 0,width2 = 0,alignment = 0,score = 0));
pVal <- vector(mode = "numeric", length(inputData$sco...
2009 Jun 10
1
Analisys in Multidimensional contingency tables
...is of multidimensional contingency
tables using R. I' working with the Agresti example where you have the
data from 3 categories. The thing is how can I do the analisys using the
G2 statistics. Somebody can send me an Idea?
I attach the program where you can find the data.
Best Regards,
> prob1<- data.frame(victim=c(rep('white',4),rep('black',4)),
+ perp=c(rep('white',2),rep('black',2),rep('white',2),rep('black',2)),
+ death=rep(c('yes','no'),4), count=c(19,132,11,52,0,9,6,97))
> prob1
victim perp death count
1 whit...
2000 Apr 05
0
My first R program
...other you guys with this syntax problem, this is my first R
program, and I seem to not have grasped something right. I keep getting
an error message from 'parse' on the line with the *** :
pValCalculator(b, n=20, m=20)
{
ind <- 1:min(c(n,m))
prob <- (1-pnorm(b,sd=std*sqrt(ind)))
prob1 <- sum((n-ind+1)*(m-ind+1)*prob)
prob1
}
inputData <-
scan("/users/lvssso/projects/LAMA/output/pValLamaScore.tmp", list(block1
= "",block2 = "",width1 = 0,width2 = 0,alignment = 0,score = 0));
pVal <- vector(mode = "numeric", length(lamaScore));...
2007 Jan 18
0
help with niave bayes
...# number of training points
n.test <- 200 # number of test points
p<-2 # dimension of input space
z <- matrix(rnorm((n+n.test)*p),ncol=p)
x <- matrix(0,nrow=n+n.test,ncol=p)
for (i in 1:p)
x[,i] <- z%*%rnorm(p)
truecoef <- c(1,2)
prob1 <- exp(x%*%truecoef)/(1+exp(x%*%truecoef))
# prob is the true probability of class 1
y <- rbinom(n+n.test,1,prob1)
# separate the data into train and test sets
mydata <- data.frame(y=y[1:n],x=x[1:n,])
mydata.test <- data.frame(y=y[n+(1:n.test)],x=x[n+(1:n.test),])
######################...
2012 Apr 04
0
multivariate ordered probit regression---use standard bivariate normal distribution?
...he model with
the two response variables separately. Any suggestions are welcome.
Again, if it helps in your response, I've included a link to the data
below. Thanks.
--Trey
Get the data (a *.csv file) here:
https://docs.google.com/open?id=0B5zZGW2utJN0TEctcW1oblFRcTJrNDVLOVBmRWRaQQ
unvar.prob1<-vglm(pube3~age,data=refdata,cumulative(link="probit",parallel=FALSE,reverse=TRUE))
> unvar.prob1
Call:
vglm(formula = pube3 ~ age, family = cumulative(link = "probit",
parallel = FALSE, reverse = TRUE), data = refdata)
Coefficients:
(Intercept):1 (Intercept):2 age:1 age:...
2002 Aug 06
3
hard to believe speed difference
...bj.nextGaussian()*sd;
if(harvest>lower && harvest<upper) break;
}
harvest = Sfun.nearestInteger(harvest);
left = (harvest - .5 - mean)/sd;
right = (harvest + .5 - mean)/sd;
double prob1 = Statistics.normalCdf(right) -
Statistics.normalCdf(left);
prob = prob1/prob2;
}
public static void main(String[] useless)
{
System.out.println(new Date());
int n = 500000;...
2007 Jul 06
0
svyglm
...all:
svyglm(q14sum ~ q16x + q17ax + q17bx + q17cx + q17dx + q17ex +
q17fx + q18x + q19x + heavy + binge + smoksum + q41sum +
q46 + exsum + q53 + q55 + q61 + ethnicgrp + pcs_sum + mcs_sum,
design = dudleyls1design, family = binomial)
Survey design:
svydesign(id = ~1, probs = ~prob1, strata = ~strat1, fpc = ~pop1,
data = dudleyls1)
Coefficients:
Estimate Std. Error t value
Pr(>|t|)
(Intercept) -0.929963 0.286259 -3.249
0.001170 **
q16xOK 0.433945 0.086506 5.01...
2009 Apr 21
4
My surprising experience in trying out REvolution's R
...);
obj <- optim(u.mean.initial, fn, control=list(fnscale=-1), hessian
= T)
u.mean.initial <- obj$par;
var.root <- solve(-obj$hessian);
var.root <- t( chol(var.root) );
u <- matrix( rnorm(n.random*n.simu), nrow=n.random, ncol=n.simu );
log.prob1 <- -colSums(u*u)/2;
u <- u.mean.initial + var.root %*% u;
ada <- exp( ada.part + z %*% u );
ada <- ada/(1+ada); #it is probability now
log.prob2 <- colSums( y*log(ada) + (1-y)*log(1-ada) );
log.prob2 <- -quadratic.form2(D.u.inv, u)/2 + log....
2019 Jun 24
1
Calculation of e^{z^2/2} for a normal deviate z
>>>>> jing hua zhao
>>>>> on Mon, 24 Jun 2019 08:51:43 +0000 writes:
> Hi All,
> Thanks for all your comments which allows me to appreciate more of these in Python and R.
> I just came across the matrixStats package,
> ## EXAMPLE #1
> lx <- c(1000.01, 1000.02)
> y0 <- log(sum(exp(lx)))
> print(y0) ## Inf