Displaying 20 results from an estimated 7000 matches similar to: "AICc"
2017 Jun 08
1
stepAIC() that can use new extractAIC() function implementing AICc
I would like test AICc as a criteria for model selection for a glm using
stepAIC() from MASS package.
Based on various information available in WEB, stepAIC() use
extractAIC() to get the criteria used for model selection.
I have created a new extractAIC() function (and extractAIC.glm() and
extractAIC.lm() ones) that use a new parameter criteria that can be AIC,
BIC or AICc.
It works as
2004 Dec 04
1
AIC, AICc, and K
How can I extract K (number of parameters) from an AIC calculation, both to
report K itself and to calculate AICc? I'm aware of the conversion from AIC ->
AICc, where AICc = AIC + 2K(K+1)/(n-K-1), but not sure of how K is calculated
or how to extract that value from either an AIC or logLik calculation.
This is probably more of a basic statistics question than an R question, but I
thank
2005 Nov 03
1
Help on model selection using AICc
Hi,
I'm fitting poisson regression models to counts of birds in
1x1 km squares using several environmental variables as predictors.
I do this in a stepwise way, using the stepAIC function. However the
resulting models appear to be overparametrized, since too much
variables were included.
I would like to know if there is the possibility of fitting models
by steps but using the AICc
2006 Jul 12
2
AICc vs AIC for model selection
Hi,
I am using 'best.arima' function from forecast package to obtain point forecast for a time series data set. The documentation says it utilizes AIC value to select best ARIMA model. But in my case the sample size very small - 26 observations (demand data). Is it the right to use AIC value for model selection in this case. Should I use AICc instead of AIC. If so how can I modify
2005 Nov 02
1
model selection based on AICc
Dear members of the list,
I'm fitting poisson regression models using stepAIC that appear to
be overparametrized. I would like to know if there is the
possibility of fitting models by steps but using the AICc instead of
AIC.
Best wishes
German Lopez
2012 Feb 13
2
R's AIC values differ from published values
Using the Cement hardening data in Anderson (2008) Model Based Inference in
the Life Sciences. A Primer on Evidence, and working with the best model
which is
lm ( y ~ x1 + x2, data = cement )
the AIC value from R is
model <- lm ( formula = y ~ x1 + x2 , data =
cement )
AIC ( model )
64.312
which can be converted to AICc by adding the bias
2005 Nov 17
3
loess: choose span to minimize AIC?
Is there an R implementation of a scheme for automatic smoothing
parameter selection with loess, e.g., by minimizing one of the AIC/GCV
statistics discussed by Hurvich, Simonoff & Tsai (1998)?
Below is a function that calculates the relevant values of AICC,
AICC1 and GCV--- I think, because I to guess from the names of the
components returned in a loess object.
I guess I could use
2005 Oct 29
2
LaTex error when creating DVI version when compiling package
Dear Listers,
I got this message when compiling a package:
* creating pgirmess-manual.tex ... OK
* checking pgirmess-manual.text ... ERROR
LaTex errors when creating DVI version.
This typically indicates Rd problems.
The message is quite explicit but I struggled a lot before understanding
that the trouble comes from a single file "selMod.rd" among 44 topics.
Even though I have
2007 May 03
3
factanal AIC?
Dear list members,
Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood?
Best regards
Jens Oehlschl?gel
The AIC calculated using summary.factanal below don't appear correct to me:
n items factors total.df rest.df model.df
2007 May 03
3
factanal AIC?
Dear list members,
Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood?
Best regards
Jens Oehlschl?gel
The AIC calculated using summary.factanal below don't appear correct to me:
n items factors total.df rest.df model.df
2006 Dec 12
1
Calculating AICc using conditional logistic regression
I have a case-control study that I'm analysing using the conditional
logistic regression function clogit from the survival package.
I would like to calculate the AICc of the models I fit using clogit.
I have a variety of scripts that can calculate AICc for models with a
logLik method, but clogit does not appear to use this method.
Is there a way I can calculate AICc from clogit in R?
Many
2011 Sep 04
2
AICc function with gls
Hi
I get the following error when I try and get the AICc for a gls regression
using qpcR:
> AICc(gls1)
Loading required package: nlme
Error in n/(n - p - 1) : 'n' is missing
My gls is like this:
> gls1
Generalized least squares fit by REML
Model: thercarnmax ~ therherbmax
Data: NULL
Log-restricted-likelihood: 2.328125
Coefficients:
(Intercept) therherbmax
1.6441405
2012 Mar 29
1
how to increase speed for function?/time efficiency of below function
i am using sarima() function as below
___________________________________________________________________________________________
sarima=function(data,p,d,q,P=0,D=0,Q=0,S=-1,tol=.001){
n=length(data)
constant=1:n
xmean=matrix(1,n,1)
if (d>0 & D>0)
fitit=arima(data, order=c(p,d,q), seasonal=list(order=c(P,D,Q),
period=S),
2004 Oct 31
2
Obtaining fitted model information
Dear list,
I am brand new to R and using Dalgaard's (2002) book Introductory Statistics with R (thus, some of my terminology may be incorrect).
I am fitting regression models and I want to use Hurvich and Tsai's AICC statistic to examine my regression models. This penalty can be expressed as: 2*npar * (n/(n-npar-1)).
While you can obtain AIC, BIC, and logLik, I want to impose the AICC
2004 Dec 17
0
behaviour of BIC and AICc code
Dear R-helpers
I have generated a suite of GLMs. To select the best model for each set, I am using the
meta-analysis approach of de Luna and Skouras (Scand J Statist 30:113-128). Simply
put, I am calculating AIC, AICc, BIC, etc., and then using whichever criterion
minimizes APE (Accumulated Prediction Error from cross-validations on all model sets)
to select models.
My problem arises where I
2011 Jul 13
3
Sum weights of independent variables across models (AIC)
Hello,
I'd like to sum the weights of each independent variable across linear
models that have been evaluated using AIC.
For example:
> library(MuMIn)
> data(Cement)
> lm1 <- lm(y ~ ., data = Cement)
> dd <- dredge(lm1, beta = TRUE, eval = TRUE, rank = "AICc")
> get.models(dd, subset = delta <4)
There are 5 models with a Delta AIC Score of
2011 Jul 26
1
nls - can't get published AICc and parameters
Hi
I'm trying to replicate Smith et al.'s
(http://www.sciencemag.org/content/330/6008/1216.abstract) findings by
fitting their Gompertz and logistic models to their data (given in
their supplement). I'm doing this as I want to then apply the
equations to my own data.
Try as a might, I can't quite replicate them. Any thoughts why are
much appreciated. I've tried contacting the
2006 Dec 16
2
question about trailing arguments in an S4 method
I'm trying to add arguments to the AIC method
for some classes -- things like
weights=TRUE to calculate AIC weights
corr=TRUE, nobs to calculate AICc
delta=TRUE to put a delta-AIC column in the output.
The problem is that AIC is defined as
AIC(object, ..., k=2) where k is the constant associated
with the penalty term and ... is a list of objects
that will have their AICs calculated
2010 Aug 17
2
how to selection model by BIC
Hi All:
the package "MuMIn" can be used to select the model based on AIC or AICc.
The code is as follows:
data(Cement)
lm1 <- lm(y ~ ., data = Cement)
dd <- dredge(lm1,rank="AIC")
print(dd)
If I want to select the model by BIC, what code do I need to use? And when
to select the best model based on AIC, what the differences between the
function "dredge" in
2006 Apr 07
1
how to run stepAIC starting with NULL model?
Hello,
I'm trying to figure out how to run the stepAIC function starting with the
NULL model. I can call the null model (e.g., lm(y ~ NULL)), but using
this object in stepAIC doesn't seem to work.
The objective is to calculate AICc. This can be done if stepAIC can be
run starting with the NULL model; the (2p(p-1)/(n-p-1))to get AICc would
be added to the final step AIC value. Can