search for: aicc

Displaying 20 results from an estimated 40 matches for "aicc".

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2007 Jan 09
min() return factor class values
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2017 Jun 08
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...
2005 Nov 17
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 optimize(), or do a simple line search on span=, but I'm not sure how to use loess.aic to write a function that would act as a wrapper for loess() and return the mimim...
2012 Feb 13
R's AIC values differ from published values
...ce 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 correction factor 2*K*(K+1)/(n-K-1) to give the AICc value of 69.312 (addition of 5, where n=13 and K=4). This same value, 69.31, can be obtained using R package AICcmodavg library ( AICcmodavg ) data (cement) cement Cand.models <- list( ) Cand.mode...
2006 Dec 12
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 thanks, Katherine Boughey -- School of Environmental Sciences Univers...
2014 Jun 26
AICc in MuMIn package
Hello, I am modelling in glmmADMB count data (I´m using a negative binomial distribution to avoid possitive overdispersion) with four fixed and one random effect. I´m also using MuMIn package to calculate the AICc and also to model averaging using the function dredge. What I do not understand is why dredge calculates a different value of the AICc and degrees of freedom than the function AICc (please see bellow). Also the logLik changes (as expected). > logLik (glmmadmb.Tot.Pr.nb) ---- 12 in model selecti...
2011 Sep 04
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 Coeffic...
2004 Dec 04
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 you for you...
2013 Mar 29
Error message in dredge function (MuMIn package) used with binary GLM
...ere's the script: globalmodel<- glm(TB~lat+protocol+tested+ streams+goats+hay+cattle+deer, family="binomial") chat<- deviance(globalmodel)/59 #There we 59 residual degrees of freedom in this global model. models<- dredge(globalmodel, beta=FALSE, evaluate=TRUE, rank="AICc", chat=chat, fixed=NULL, trace=FALSE) And the error message is: Error in UseMethod("logLik") : no applicable method for 'logLik' applied to an object of class "logical" I have trawled the literature and it seems to be ok to use a binary GLM as the global model...
2006 Jul 12
AICc vs AIC for model selection
...m 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 best.arima function to change the selection creteria? Any pointers would be of great help. Thanx in advance. Sachin --------------------------------- [[alternative HTML version deleted]]
2013 Apr 16
Model ranking (AICc, BIC, QIC) with coxme regression
Hi, I'm actually trying to rank a set of candidate models with an information criterion (AICc, QIC, BIC). The problem I have is that I use mixed-effect cox regression only available with the package {coxme} (see the example below). #Model1 >spring.cox <- coxme (Surv(start, stop, Real_rand) ~ strata(Paired)+R4+R3+R2+(R3|Individual), spring) I've already found some explications i...
2010 Jun 25
Confused: Looping in dataframes
Hey, I have a data frame x which consists of say 10 vectors. I essentially want to find out the best fit exponential smoothing for each of the vectors. The problem while I'm getting results when i say > lapply(x,ets) I am getting an error when I say >> myprint function(x) { for(i in 1:length(x)) { ets(x[i],model="AZZ",opt.crit=c("amse")) } } The error message is
2007 Nov 08
Help me please...Large execution time in auto.arima() function
...cessor Intel Core2 Duo T7300 and 2Gb of RAM. fit_2323v_168f<-auto.arima(regts.ts, d = 1, D = 1, max.p = 2, max.q = 2, max.P = 1, max.Q = 1, max.order = 5, start.p=0, start.q=0, start.P=0, start.Q=0, stationary = FALSE, ic = c("aic","aicc", "bic"), stepwise=TRUE, trace=TRUE) It is any configuration to speed-up this? Thanks in advance! Jo?o Santos -- View this message in context:
2006 Apr 07
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 anyone suggest how to run stepAIC beginning with the NULL model, and sequentially adding and removing variables (essentially a bottom-up approa...
2011 Oct 25
difficulties with MuMIn model generation with coxph
Hi All, I'm having trouble with the automatized model generation (dredge) function in the MuMIn package. I'm trying to use it to automatically generate subsets of models from a global cox proportional hazards model, and rank them based on AICc. These seems like it's possible, and the Mumin documentation says that coxph is supported. However, when I run the code (see below), it gives me the following error message: Error in UseMethod("logLik") : no applicable method for 'logLik' applied to an object of class &quo...
2009 Feb 25
indexing model names for AICc table
hi folks, I'm trying to build a table that contains information about a series of General Linear Models in order to calculate Akaike weights and other measures to compare all models in the series. i have an issue with indexing models and extracting the information (loglikehood, AIC's, etc.) that I need to compile them into the table. Below is some sample code that illustrates my
2011 Jul 13
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 less than 4. I would like to sum the weights for each of the independent variables across the five models. How can I do that? Thanks, Mike
2011 May 10
Series temporales
...a.frame(Tipologia = numeric(0), Provincia = numeric(0), AnoModelo = numeric(0), ecuacion =character(0), aicc = numeric(0), bic =numeric(0), sigma2 = numeric(0), loglik = numeric(0), coeficientes = character(),...
2004 Feb 18
Generalized Estimating Equations and log-likelihood calculation
Hi there, I'm working with clustered data sets and trying to calculate log-likelihood (and/or AIC, AICc) for my models. In using the gee and geese packages one gets Wald test output; but apparently there is no no applicable method for "logLik" (log-likelihood)calculation. Is anyone aware of a way to calculate log-likelihood for GEE models? Thanks for the help, Bruce
2005 Jul 03
code for model-averaging by Akaike weights
Dear all, does anyone have r code to perform model-averaging of regression parameters by Akaike weights, and/or to do all-possible-subsets lm modelling that reports parameter estimates, AICc and number of parameters for each model? I have been looking for these in the archive but found none. (I am aware that many of you would warn me against these methods advocated by Burnham and Anderson 2002, please do not.) Thank you, VB -----------------------------------------------------...