Displaying 20 results from an estimated 1000 matches similar to: "About object of class mle returned by user defined functions"
2004 Dec 13
1
AIC, glm, lognormal distribution
I'm attempting to do model selection with AIC, using a glm and a lognormal
distribution, but:
fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian(link="log"))
## gives the same result as either of the following:
fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian)
fit1<-lm(BA~Year,data=pdat.sp1.65.04)
fit1
#Coefficients:
#(Intercept) Year2004
# -1.6341
2013 Nov 14
1
issues with calling predict.coxph.penal (survival) inside a function
Thanks for the reproducable example. I can confirm that it fails on my machine using
survival 2-37.5, the next soon-to-be-released version,
The issue is with NextMethod, and my assumption that the called routine inherited
everything from the parent, including the environment chain. A simple test this AM showed
me that the assumption is false. It might have been true for Splus. Working this
2006 Jun 23
1
How to use mle or similar with integrate?
Hi
I have the following formula (I hope it is clear - if no, I can try to
do better the next time)
h(x, a, b) =
integral(0 to pi/2)
(
(
integral(D/sin(alpha) to Inf)
(
(
f(x, a, b)
)
dx
)
dalpha
)
and I want to do an mle with it.
I know how to use mle() and I also know about integrate(). My problem is
to give the parameter values a and b to the
2011 Mar 20
3
manova question
Dear friends,
Sorry for this somewhat generically titled posting but I had a question
with using contrasts in a manova context. So here is my question:
Suppose I am interested in doing inference on \beta in the case of the
model given by:
Y = X %*% \beta + e
where Y is a n x p matrix of observations, X is a n x m design matrix,
\beta is m x p matrix of parameters, and e is a
2009 Sep 07
1
Omnibus test for main effects in the face of an interaction containing the main effects.
R 2.9.1
Windows XP
I am fitting a random effects ANOVA with two factors Group which has two levels and Time which has three levels:
fita<-lme(Post~Time+factor(Group)+factor(Group)*Time, random=~1|SS,data=blah$alldata)
I want to get the omnibus significance tests for each factor and the interaction. I believe I can get the omnibus test for the interaction by running the model:
2009 Sep 08
3
Omnibus test for main effects in the face ofaninteraction containing the main effects.
Daniel,
When Group is entered as a factor, and the factor has two levels, the
ANOVA table gives a p value for each level of the factor. What I am
looking for is the omnibus p value for the factor, i.e. the test that
the factor (with all its levels) improves the prediction of the outcome.
You are correct that normally one could rely on the fact that the model
2009 Feb 01
2
Extracting Coefficients and Such from mle2 Output
The mle2 function (bbmle library) gives an example something like the
following in its help page. How do I access the coefficients, standard
errors, etc in the summary of "a"?
> x <- 0:10
> y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8)
> LL <- function(ymax=15, xhalf=6)
+ -sum(stats::dpois(y, lambda=ymax/(1+x/xhalf), log=TRUE))
> a <- mle2(LL,
2016 Jan 18
2
how to flush user input before READ()
On Mon, 18 Jan 2016, Ethy H. Brito wrote:
>> how to flush user input before READ()?
How about a read() to a dummy variable with a 1 second timeout to consume
the octothorpe and password?
--
Thanks in advance,
-------------------------------------------------------------------------
Steve Edwards sedwards at sedwards.com Voice: +1-760-468-3867 PST
2013 Feb 08
3
On p-values presented in the summary of Linear Models
Dear list members
I have a doubt on how p-values for t-statistics are calculated in the
summary of Linear Models.
Here goes an example:
x <- rnorm(100,50,10)
y <- rnorm(100,0,5)
fit1<-lm(y~x)
summary(fit1)
summary(fit1)$coef[2] # b
summary(fit1)$coef[4] # Std. Error
summary(fit1)$coef[6] # t-statistic
summary(fit1)$coef[8] # Pr(>|t|
summary(fit1)$df [2] # degrees of freedom
#
2003 May 22
1
list W2K shares
Hi all
I'am trying to list the shares of our W2K server and got this error
message.
$ smbclient -L cvl
added interface ip=192.168.100.1 bcast=255.255.255.255 nmask=0.0.0.0
session request to CVL failed (Called name not present)
Password:
Anonymous login successful
Domain=[CVL-SERVER-1] OS=[Windows 5.0] Server=[Windows 2000 LAN Manager]
tree connect failed:
2006 Jan 26
8
nat table remenbering nat''s
Dear All
Why NAT rules stays valid even if I flush nat anf table chains??
I have:
iptables -P FORWARD DROP
iptables -A FORWARD -m state --state ESTABLISHED,RELATED -j ACCEPT
iptables -A FORWARD -s SOME_IP -d SOME_BCP_5_IP --dport 1234 -j ACCEPT
iptables -i nat -A PREROUTING -s SOME_IP -d MY_INTERNET_IP \\
--dport 1234 -j DNAT --to-destination SOME_BCP_5_IP
The conection is
2012 Nov 08
2
Comparing nonlinear, non-nested models
Dear R users,
Could somebody please help me to find a way of comparing nonlinear, non-nested
models in R, where the number of parameters is not necessarily different? Here
is a sample (growth rates, y, as a function of internal substrate
concentration, x):
x <- c(0.52, 1.21, 1.45, 1.64, 1.89, 2.14, 2.47, 3.20, 4.47, 5.31, 6.48)
y <- c(0.00, 0.35, 0.41, 0.49, 0.58, 0.61, 0.71, 0.83, 0.98,
2009 Apr 15
2
AICs from lmer different with summary and anova
Dear R Helpers,
I have noticed that when I use lmer to analyse data, the summary function
gives different values for the AIC, BIC and log-likelihood compared with the
anova function.
Here is a sample program
#make some data
set.seed(1);
datx=data.frame(array(runif(720),c(240,3),dimnames=list(NULL,c('x1','x2','y'
))))
id=rep(1:120,2); datx=cbind(id,datx)
#give x1 a
2011 Mar 25
2
A question on glmnet analysis
Hi,
I am trying to do logistic regression for data of 104 patients, which
have one outcome (yes or no) and 15 variables (9 categorical factors
[yes or no] and 6 continuous variables). Number of yes outcome is 25.
Twenty-five events and 15 variables mean events per variable is much
less than 10. Therefore, I tried to analyze the data with penalized
regression method. I would like please some of the
2011 Jan 24
5
Train error:: subscript out of bonds
Hi,
I am trying to construct a svmpoly model using the "caret" package (please
see code below). Using the same data, without changing any setting, I am
just changing the seed value. Sometimes it constructs the model
successfully, and sometimes I get an ?Error in indexes[[j]] : subscript out
of bounds?.
For example when I set seed to 357 following code produced result only for 8
2004 Jun 11
1
comparing regression slopes
Dear List,
I used rlm to calculate two regression models for two data sets (rlm
due to two outlying values in one of the data sets). Now I want to
compare the two regression slopes. I came across some R-code of Spencer
Graves in reply to a similar problem:
http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html
The code was:
> df1 <- data.frame(x=1:10, y=1:10+rnorm(10))
2008 Feb 23
3
using subset() in data frame
R folks,
As an R novice, I struggle with the mystery of subsetting. Textbook and
online examples of this seem quite straightforward yet I cannot get my
mind around it. For practice, I'm using the code in MASS Ch. 6,
"whiteside data" to analyze a different data set with similar variables
and structure.
Here is my data frame:
###subset one of three cases for the variable
2020 Sep 29
5
2 KM curves on the same plot
Hello,
Can anyone suggest a simple way to generate a Kaplan-Meier plot with 2 survfit objects, just like this one:?
https://drive.google.com/file/d/1fEcpdIdE2xYtA6LBQN9ck3JkL6-goabX/view?usp=sharing
Suppose I have 2 survfit objects: fit1 is for the curve on the left (survtime has been truncated to the cutoff line: year 5), fit2 is for the curve on the right (minimum survival time is at the
2011 Oct 06
1
anova.rq {quantreg) - Why do different level of nesting changes the P values?!
Hello dear R help members.
I am trying to understand the anova.rq, and I am finding something which I
can not explain (is it a bug?!):
The example is for when we have 3 nested models. I run the anova once on
the two models, and again on the three models. I expect that the p.value
for the comparison of model 1 and model 2 would remain the same, whether or
not I add a third model to be compared
2008 Jul 02
1
survival package test stats
Hello,
Is there a function in the survival package that will allow me to test a subset of independent variables for joint significance? I am thinking along the lines of a Wald, likelihood ratio, or F-test. I am using the survreg procedure to estimate my parameters. Thank you.
Geoff
Geoffrey Smith
Visiting Assistant Professor
Department of Finance
University of Illinois at Urbana-Champaign