Displaying 19 results from an estimated 19 matches for "gamma2".
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2009 Jun 05
2
p-values from VGAM function vglm
Anyone know how to get p-values for the t-values from the coefficients
produced in vglm?
Attached is the code and output ? see comment added to output to show
where I need p-values
+ print(paste("********** Using VGAM function gamma2 **********"))
+ modl2<-
vglm(MidPoint~Count,gamma2,data=modl.subset,trace=TRUE,crit="c")
+ print(coef(modl2,matrix=TRUE))
+ print(summary(modl2))
[1] "********** Using VGAM function gamma2 **********"
VGLM linear loop 1 : coefficients =
0.40846460...
2016 Apr 18
0
R [coding : do not run for every row ]
...apply functions.
>
> result <- apply(
> all_combine1,
> 1,
> function(x){
> p.value <- sapply(
> seq_len(nSims),
> function(sim){
> gamma1 <- rgamma(x["m"], x["sp(skewness1.5)"], x["scp1"])
> gamma2 <- rgamma(x["n"], x["scp1"], 1)
> gamma1 <- gamma1 - x["sp(skewness1.5)"] * x["scp1"]
> gamma2 <- gamma2 - x["sp(skewness1.5)"]
> c(
> equal = t.test(gamma1, gamma2, var.equal=TRUE)$p.value,
>...
2016 Apr 18
0
R [coding : do not run for every row ]
...d column
> m<-all_combine1[ss,1]
> n<-all_combine1[ss,2]
>
> for (sim in 1:nSims)
> {
> #generate 2 random samples from gamma distribution with equal skewness
> gamma1<-rgamma(m,all_combine1[ss,3],all_combine1[ss,4])
> gamma2<-rgamma(n,all_combine1[ss,4],1)
>
> # minus the population mean to ensure that there is no lose of equality of mean
> gamma1<-gamma1-all_combine1[ss,3]*all_combine1[ss,4]
> gamma2<-gamma2-all_combine1[ss,3]
>
> #extract p-value out and stor...
2009 Jun 26
1
predicted values after fitting gamma2 function
...tance,
breaks=Max.brks,plot=FALSE )
Max.cnt<-as.data.frame(cbind(sim,Max.f$mids,Max.f$counts))
colnames(Max.cnt)<-c("Simulation","MidPoint","Count")
then I fit this to a gamma distribution function:
modl<-
vglm
(Count
~
MidPoint
,gamma2
,data
=subset(Max.cnt,select=(simulation,MidPoint,Count),trace=TRUE,crit="c")
print(coef(modl2,matrix=TRUE))
print(summary(modl2))
This produces the output:
VGLM linear loop 1 : coefficients =
3.231473495, 0.597085743, -0.195591168
...
VGLM linear loop 20 : coeffici...
2016 Apr 18
3
R [coding : do not run for every row ]
...d column
> m<-all_combine1[ss,1]
> n<-all_combine1[ss,2]
>
> for (sim in 1:nSims)
> {
> #generate 2 random samples from gamma distribution with equal skewness
> gamma1<-rgamma(m,all_combine1[ss,3],all_combine1[ss,4])
> gamma2<-rgamma(n,all_combine1[ss,4],1)
>
> # minus the population mean to ensure that there is no lose of equality of mean
> gamma1<-gamma1-all_combine1[ss,3]*all_combine1[ss,4]
> gamma2<-gamma2-all_combine1[ss,3]
>
> #extract p-value out and stor...
2016 Apr 18
0
R [coding : do not run for every row ]
You can make this much more readable with apply functions.
result <- apply(
all_combine1,
1,
function(x){
p.value <- sapply(
seq_len(nSims),
function(sim){
gamma1 <- rgamma(x["m"], x["sp(skewness1.5)"], x["scp1"])
gamma2 <- rgamma(x["n"], x["scp1"], 1)
gamma1 <- gamma1 - x["sp(skewness1.5)"] * x["scp1"]
gamma2 <- gamma2 - x["sp(skewness1.5)"]
c(
equal = t.test(gamma1, gamma2, var.equal=TRUE)$p.value,
unequal = t.t...
2016 Apr 17
2
R [coding : do not run for every row ]
...samples from the first column and second column
m<-all_combine1[ss,1]
n<-all_combine1[ss,2]
for (sim in 1:nSims)
{
#generate 2 random samples from gamma distribution with equal skewness
gamma1<-rgamma(m,all_combine1[ss,3],all_combine1[ss,4])
gamma2<-rgamma(n,all_combine1[ss,4],1)
# minus the population mean to ensure that there is no lose of equality of mean
gamma1<-gamma1-all_combine1[ss,3]*all_combine1[ss,4]
gamma2<-gamma2-all_combine1[ss,3]
#extract p-value out and store every p-value into matrix...
2016 Apr 19
0
problem on simulation code (the loop unable to function effectively)
...amples from the first column and second column
> m<-all[ss,1]
> n<-all[ss,2]
>
> for ( sim in 1:nSims)
> {
> #generate 2 random samples from gamma distribution with equal
> skewness
> gamma1<-rgamma(m,16/9,all[ss,3])
> gamma2<-rgamma(n,16/9,1)
> #minus population mean from each sample to maintain the equality of
> null #hypotheses (population mean =scale parameter *shape
> parameter)
> gamma1<-gamma1-16/9*all[ss,3]
> gamma2<-gamma2-16/9
>
> matrix3_equal[sim,1]<-t.test(gamma1...
2009 Jun 16
0
Generation from COX PH with gamma frailty
...anks in advance.
Aysun
> Anyone know how to get p-values for the t-values from the coefficients
> produced in vglm?
> Attached is the code and output ? see comment added to output to show
> where I need p-values
>
>
> + print(paste("********** Using VGAM function gamma2 **********"))
> + modl2<-
> vglm(MidPoint~Count,gamma2,data=modl.subset,trace=TRUE,crit="c")
> + print(coef(modl2,matrix=TRUE))
> + print(summary(modl2))
>
>
> [1] "********** Using VGAM function gamma2 **********"
> VGLM linear l...
2016 Apr 19
0
problem on simulation code (the loop unable to function effectively)
...ll[ss,1]
>>> n<-all[ss,2]
>>>
>>> for ( sim in 1:nSims)
>>> {
>>> #generate 2 random samples from gamma distribution with equal
>>> skewness
>>> gamma1<-rgamma(m,16/9,all[ss,3])
>>> gamma2<-rgamma(n,16/9,1)
>>> #minus population mean from each sample to maintain the equality of
>>> null #hypotheses (population mean =scale parameter *shape
>>> parameter)
>>> gamma1<-gamma1-16/9*all[ss,3]
>>> gamma2<-gamma2-16/9
>>>...
2011 Jun 07
0
WinBUGS on survival, simple but confusing question
...nto WinBUGS
surt.BUGS = surt;
surt.BUGS[surt >= surt.cens] = NA;
if(any(is.na(surt.BUGS))) cat("surt.BUGS taking NA (censored) value at",
which(is.na(surt.BUGS)), ".\n");
surt.cens.BUGS = surt.cens;
surt.cens.BUGS[surt < surt.cens] = 0;
## non-info prior
sd.gamma1 = sd.gamma2 = 1e-2;
pos.lim = 1e-4;
norm.sd = 1e-3;
BUGS.data = list("N", "Treat", "surt.BUGS", "surt.cens.BUGS", "sd.gamma1",
"sd.gamma2", "norm.sd", "pos.lim");
BUGS.parameters = c("alpha", "surt.sigma", &qu...
2004 Jun 12
2
ordered probit or logit / recursive regression
...pirical mean and standard deviation for each variable,
plus standard error of the mean:
Mean SD Naive SE Time-series SE
(Intercept) 1.10010 0.1580 0.002497 0.003518
x1 0.09309 0.1238 0.001958 0.001953
x2 -0.53336 0.1194 0.001887 0.001943
gamma2 1.08807 0.1565 0.002474 0.004187
gamma3 1.54971 0.1818 0.002875 0.004952
2. Quantiles for each variable:
2.5% 25% 50% 75% 97.5%
(Intercept) 0.8037 0.99397 1.09560 1.2053 1.4253
x1 -0.1503 0.01075 0.09285 0.1784 0.3393
x2...
2009 Apr 11
2
who happenly read these two paper Mohsen Pourahmadi (biometrika1999, 2000)
...I really can get the same or close output as he did,so,any one who
have happenly read his paper,got any idea how he got the LS estimates of
gamma.
he assumed the autoregressive phi_tj satisfy the cubic function on lag of
time,where t is from 1 to 11,j from 1 to t-1,his model is:
phi_tj=gamma1+gamma2*(t-j)+gamma3*(t-j)^2+gamma4*(t-j)^3, #biometrika
1999,page685
at first moment ,I thougt my design matrix should be
1 1 1 1
1 2 4 8
1 3 9 27.....
but I found this is wrong,actually I should(I think) use a polynomial design
matirx with level of 11,degree=3
here is my rocode~~
y1=c(1,...
2012 Dec 04
1
Solve system of equations (nleqslv) only returns origin
...600
theta=0.6
psale=0.6
mu=psale*(1-theta)
alphah=0.15
Cg=6240
Cs=2820
A= 100
D=0.0001
greekp=0.43
K=100000
##### Species Parameters ##########
b1=0.38
p1=16654
v1 = 0.28
N1=6000
g1=1
delta1=1
b2=0.4
p2=2797
v2 = 0.31
N2=10000
g2=1
delta2=1
### Define functions with vector x = c(Lg, Ls, gamma1, gamma2, lamda)
firstordercond <- function (x) {
y=numeric(4)
y[1]=(alphah/x[3])-(x[5]*((p1-(((theta+mu)*(((N1/A)*g1^greekp*x[1]^b1)+K))+((theta+mu)*(((1-exp(-2*D*v1*N1))*x[2])+K))))*(((N1/A)*g1^(greekp))*x[1]^b1+(2*v1*N1*D)*x[2])
+
delta1*theta*(((N1/A)*g1^(greekp))*x[1]^b1+(2*v1*N1*D)*x[...
2002 Apr 22
3
glm() function not finding the maximum
...w, and
didn't find the maximum.
The data set and code for the two methods of estimation are included
below. I don't think I am making a mistake here. Sorry if I have.
Thanks
Richard
> gamma1(data) #uses the glm() function
$loglik
[1] 875.4274
$par
[1] 9.572403e-02 4.345771e+03
> gamma2(data) #"by hand" using optim()
$loglik
[1] 793.3913
$par
[1] 0.518145 802.854297
#Data set
data_c(51.47, 210.19, 49.55, 61.93, 60.61, 744.57, 338.59, 133.93,
191.57, 111.43, 432.83, 185.23, 155.61, 84.72, 120.2, 15.33,
77.05, 115.77, 25.23, 657.94, 108.39, 61.08, 142.42, 87.86, 272.87...
2007 May 08
0
Question on bivariate GEE fit
...le say,
i have the data frame with column names
var1 var2 Unit time trt
(trt represents the treatment)
Now suppose I want to fit a joint model of the form for the *i* th unit
var1jk = alpha1 + beta1*timejk + gamma1* trtjk + delta1* timejk:trtjk +
error1jk
var2 = alpha2 + beta2*timejk + gamma2* trtjk + delta2* timejk:trtjk +
error2jk
where j index time and k index the treatment received
Using indicator variables I have been able to fit and run the code for
a bivariate model using unstructured covariance matrix. However,
I want to fit a model for a structured variance covariance matrix....
2007 Feb 17
1
Solve in maximum likelihood estimation
...sum(-log.lik)
}
kalman(c(theta,kappa,sqrt(Q),sqrt(R)))
startwerte <- c(theta,kappa,sqrt(Q),sqrt(R))
optim(startwerte*0.9,kalman,method="SANN")
c(theta,kappa,sqrt(Q),sqrt(R))
#nlmestimate$estimate
Rprof(NULL)
gamma2 <- summaryRprof()
_________________________________________________________________
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2006 Oct 27
0
VGAM package released on CRAN
...Frank's Bivariate Distribution Family Function
frechet2 Frechet Distribution Family Function
freund61 Freund's (1961) Bivariate Extension of the
Exponential Distribution
gamma1 1-parameter Gamma Distribution
gamma2 2-parameter Gamma Distribution
gammahyp Gamma Hyperbola Bivariate Distribution
gaussianff Gaussian (normal) Family Function
genbetaII Generalized Beta Distribution of the Second Kind
genpoisson Generalized Poisson distribution...
2005 May 25
3
Speex on TI C6x, Problem with TI C5x Patch
...st->mode=m;
st->frameSize = mode->frameSize;
st->windowSize = st->frameSize*3/2;
st->nbSubframes=mode->frameSize/mode->subframeSize;
st->subframeSize=mode->subframeSize;
st->lpcSize = mode->lpcSize;
st->gamma1=mode->gamma1;
st->gamma2=mode->gamma2;
st->min_pitch=mode->pitchStart;
st->max_pitch=mode->pitchEnd;
st->lag_factor=mode->lag_factor;
st->lpc_floor = mode->lpc_floor;
st->submodes=mode->submodes;
st->submodeID=st->submodeSelect=mode->defaultSubmode;
st->bou...