Displaying 10 results from an estimated 10 matches for "n_j".
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2013 Aug 27
1
Error in simulation. NAN
...inpack.h>
#include <R_ext/Lapack.h>
#include <R_ext/BLAS.h>
#include "funzioni.h"
#define _USE_MATH_DEFINES
extern "C" {
SEXP Model1_imp11Cpp(
SEXP ad_start_r, SEXP ad_end_r, SEXP ad_esp_r,
SEXP burnin_r, SEXP thin_r,SEXP iter_1_r,SEXP iter_2_r,
SEXP n_j_r,SEXP J_r,
SEXP prior_alpha_r,SEXP prior_rho_r,SEXP prior_sigma2_r,SEXP
prior_phi_r,SEXP prior_zeta2_r,
SEXP sdprop_rho_r,SEXP sdprop_sigma2_r,
SEXP start_alpha_r,SEXP start_mu_r,SEXP start_rho_r,SEXP
start_sigma2_r,SEXP start_k_r,SEXP start_phi_r, SEXP start_zeta2_r,
SEXP x_r,SEXP H...
2005 Nov 29
1
rlogis() in simulation
...and for the student effect to be 1.45 as
I describe above? You can see my erroneous code below.
Thanks,
Harold
## Note, the subscripts are a little messy as I am changing some
notation. But it should be transparent (I hope)
N <- 5000 # Number of students
J <- 50 # Number of schools
N_j <- N/J # Number of students in each school
rps <- rep(N_j, J)
error <- matrix(numeric(N * 40), ncol = 40)
for(i in 1:40){
e_gik <- rlogis(N, 0, sqrt(1.7-.25) )
e_gk <- rep(rlogis(J, 0, sqrt(.25) ), rps)
error[,i] <- e_gk + e_gik
}
Windows XP
platform i386-pc-mingw32
a...
2005 Dec 01
1
Simulate Correlated data from complex sample
...39;ve used RSiteSearch() a bit, but the keywords I'm using aren't
turning up results that I can use. I may be missing something very
simple and transparent.
Any thoughts are much appreciated,
Harold
Ver 2.2
Windows XP
N <- 5000 # Number of students
J <- 50 # Number of schools
N_j <- N/J # Number of students in each school
a_g <- c(0,.5,1) # This is the growth vector
# Step 1 -- create psi for base grade
rps <- rep(N_j, J)
v_gk <- rep(rnorm(J, 0, sqrt(.01) ), rps)
v_gik <- rnorm(N, 0, sqrt(.99))
# Organize into a dataframe
data <- data.frame(schid = re...
2008 Aug 15
2
Design-consistent variance estimate
...\left[\frac{\partial f(Y)}{Y}\right]^2 var(Y)
\end{equation}
\noindent where
\begin{equation}
\left[\frac{\partial f(Y)}{Y}\right] = \frac{1}{N}
\end{equation}
\begin{equation}
var(Y) = \frac{k}{k-1} \sum_{j=1}^k(\hat{Y}_j-\hat{Y}_{..})^2
\end{equation}
\begin{equation}
\hat{Y}_j = \sum_{i=1}^{n_j}\hat{Y}_{j(i)}
\end{equation}
\begin{equation}
\hat{Y}_{..} = k^{-1} \sum_{j=1}^k \hat{Y}_j
\end{equation}
\noindent where $j$ indexes cluster $(1, 2, \ldots, k)$, $j(i)$ indexes
the $i$th member of cluster $j$, and $n_j$ is the total number of
members in cluster $j$. The standard error is then t...
2000 May 03
0
Combinatorics for nonparametric tests
..._cbind(p,i)
v_c(1:i,1:(i-1))
for(j in 2:i){v_v[-1]
p_rbind(p,pp[,v[1:i]])}}
p}
Until now I hesitated to dwell on writing functions to generate all
n!/(k!(n-k)!) k-combinations of an n-element set or more generally all
n!/(k_1!k_2!...n_k!) choices of placing n objects into k boxes where
box j has n_j objects.
Not intending to re-invent the wheel I turn to the R community to ask
if someone has already written these functions.
Any help is thankfully appreciated.
--- D.Trenkler ---
************************************************************************
*********
Dietrich Trenkler
(trenk...
2011 Jan 03
1
Greetings. I have a question with mixed beta regression model in nlme.
*Dear R-help:
My name is Rodrigo and I have a question with nlme package
in R to fit a mixed beta regression model. The details of the model are:
Suppose that:*
*j in {1, ..., J}* *(level 1)*
*i in {1, ..., n_j}* *(level 2)*
*y_{ij} ~ Beta(mu_{ij} * phi_{ij}; (1 - mu_{ij}) * phi_{ij})
y_{ij} = mu_{ij} + w_{ij}
*
*with*
*logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b2 * x2_{ij}
log(phi_{ij}) = Gamma_{0i} + Gamma_{1i} * z1_{ij} + c2 * z2_{ij}
*
*Beta_{0i} = b_0 + u_{0i}
Beta_{1i} = b_1 + u_{1i}
Gam...
2011 Jan 03
0
Greetings. I have a question with mixed beta regression model in nlme (corrected version).
...nlme package
in R to fit a mixed beta regression model. I'm so sorry. In the last
email, I forgot to say that W is also a unknown parameter in the mixed
beta regression model. In any case, here I send you the correct formulation.
**
Suppose that:*
*j in {1, ..., J}* *(level 1)*
*i in {1, ..., n_j}* *(level 2)*
*y_{ij} ~ Beta(mu_{ij} * phi_{ij}; (1 - mu_{ij}) * phi_{ij})
y_{ij} = mu_{ij} + w_{ij}
*
*with*
*logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b_2 * x2_{ij}
log(phi_{ij}) = Gamma_{0i} + Gamma_{1i} * z1_{ij} + c_2 * z2_{ij}
*
*Beta_{0i} = b_0 + u_{0i}
Beta_{1i} = b_1 + u_{1i}
G...
2003 Oct 05
2
Jonckheere-Terpstra test
Hello,
can anybody here explain what a Jonckheere-Terpstra test is and whether it is
implemented in R? I just know it's a non-parametric test, otherwise I've no
clue about it ;-( . Are there alternatives to this test?
thanks for help,
Arne
2006 May 20
1
(PR#8877) predict.lm does not have a weights argument for newdata
Dear R developers,
I am a little disappointed that my bug report only made it to the
wishlist, with the argument:
Well, it does not say it has.
Only relevant to prediction intervals.
predict.lm does calculate prediction intervals for linear models from
weighted regression, so they should be correct, right?
As far as I can see they are bound to be wrong in almost all cases, if
no weights
2011 Aug 25
1
Syntax for a three-level logistic model
Dear People at R help, I am trying to figure out the syntax for a three-level logistic model with a single random effect (intercept):
Data Collected
My data consist of three levels: level 1 is four setting for each student (setting nested within student), and each student is registered in one of 14 universities (students nested within university). More detailed:
A. 2,479 students who have a