Displaying 20 results from an estimated 70000 matches similar to: "glmnet package: command meanings"
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
2013 Jul 17
1
glmnet on Autopilot
Dear List,
I'm running simulations using the glmnet package. I need to use an
'automated' method for model selection at each iteration of the simulation.
The cv.glmnet function in the same package is handy for that purpose.
However, in my simulation I have p >> N, and in some cases the selected
model from cv.glmet is essentially shrinking all coefficients to zero. In
this case,
2012 Mar 21
2
glmnet: obtain predictions using predict and also by extracting coefficients
All,
For my understanding, I wanted to see if I can get glmnet predictions
using both the predict function and also by multiplying coefficients
by the variable matrix. This is not worked out. Could anyone suggest
where I am going wrong?
I understand that I may not have the mean/intercept correct, but the
scaling is also off, which suggests a bigger mistake.
Thanks for your help.
Juliet Hannah
2011 May 28
1
Questions regrading the lasso and glmnet
Hi all. Sorry for the long email. I have been trying to find someone local to work on this with me, without much luck. I went in to our local stats consulting service here, and the guy there told me that I already know more about model selection than he does. :-< He pointed me towards another professor that can perhaps help, but that prof is busy until mid-June, so I want to get as much
2012 Jul 12
1
using glmnet for the dataset with numerical and categorical
Dear R users,
if all my numerical variables in my datasets having the same units, may I
leave them unnormalized, just do cv.glmnet
directly(cv.glmnet(data,standardize=FALSE))?
i know normally if there is a mixture of numerical and categorical , one has
to standardize the numerical part before applying cv.glmnet with
standardize=fase, but that's due to the different units in the numerical
2013 Mar 02
0
glmnet 1.9-3 uploaded to CRAN (with intercept option)
This update adds an intercept option (by popular request) - now one can fit a model without an intercept
Glmnet is a package that fits the regularization path for a number of generalized linear models, with with "elastic net"
regularization (tunable mixture of L1 and L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast.
The current list of models covered are:
2013 Mar 02
0
glmnet 1.9-3 uploaded to CRAN (with intercept option)
This update adds an intercept option (by popular request) - now one can fit a model without an intercept
Glmnet is a package that fits the regularization path for a number of generalized linear models, with with "elastic net"
regularization (tunable mixture of L1 and L2 penalties). Glmnet uses pathwise coordinate descent, and is very fast.
The current list of models covered are:
2010 Nov 04
0
glmnet_1.5 uploaded to CRAN
This is a new version of glmnet, that incorporates some bug fixes and
speedups.
* a new convergence criterion which which offers 10x or more speedups for
saturated fits (mainly effects logistic, Poisson and Cox)
* one can now predict directly from a cv.object - see the help files for cv.glmnet
and predict.cv.glmnet
* other new methods are deviance() for "glmnet" and coef() for
2012 Mar 20
2
cv.glmnet
Hi, all:
Does anybody know how to avoid the intercept term in cv.glmnet coefficient?
When I say "avoid", it does not mean using coef()[-1] to omit the printout
of intercept, it means no intercept at all when doing the analysis. Thanks.
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2012 May 07
1
estimating survival times with glmnet and coxph
Dear all,
I am using glmnet (Coxnet) for building a Cox Model and
to make actual prediction, i.e. to estimate the survival function S(t,Xn) for a
new subject Xn. If I am not mistaken, glmnet (coxnet) returns beta, beta*X and
exp(beta*X), which on its own cannot generate S(t,Xn). We miss baseline
survival function So(t).
Below is my code which takes beta coefficients from
glmnet and creates coxph
2008 Jun 02
0
New glmnet package on CRAN
glmnet is a package that fits the regularization path for linear, two-
and multi-class logistic regression
models with "elastic net" regularization (tunable mixture of L1 and L2
penalties).
glmnet uses pathwise coordinate descent, and is very fast.
Some of the features of glmnet:
* by default it computes the path at 100 uniformly spaced (on the log
scale) values of the
2008 Jun 02
0
New glmnet package on CRAN
glmnet is a package that fits the regularization path for linear, two-
and multi-class logistic regression
models with "elastic net" regularization (tunable mixture of L1 and L2
penalties).
glmnet uses pathwise coordinate descent, and is very fast.
Some of the features of glmnet:
* by default it computes the path at 100 uniformly spaced (on the log
scale) values of the
2013 Jul 06
1
problem with BootCV for coxph in pec after feature selection with glmnet (lasso)
Hi,
I am attempting to evaluate the prediction error of a coxph model that was
built after feature selection with glmnet.
In the preprocessing stage I used na.omit (dataset) to remove NAs.
I reconstructed all my factor variables into binary variables with dummies
(using model.matrix)
I then used glmnet lasso to fit a cox model and select the best performing
features.
Then I fit a coxph model
2011 Nov 01
1
predict for a cv.glmnet returns an error
Hi there,
I am trying to use predict() with an object returned by cv.glmnet(), and get
the following error:
no applicable method for 'predict' applied to an object of class "cv.glmnet"
What's wrong?
my code:
x=matrix(rnorm(100*20),100,20)
y=rnorm(100)
cv.fit=cv.glmnet(x,y)
predict(cv.fit,newx=x[1:5,])
coef(cv.fit)
Thanks so much,
Asaf
--
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2010 Apr 04
0
Major glmnet upgrade on CRAN
glmnet_1.2 has been uploaded to CRAN.
This is a major upgrade, with the following additional features:
* poisson family, with dense or sparse x
* Cox proportional hazards family, for dense x
* wide range of cross-validation features. All models have several criteria for cross-validation.
These include deviance, mean absolute error, misclassification error and "auc" for logistic or
2010 Apr 04
0
Major glmnet upgrade on CRAN
glmnet_1.2 has been uploaded to CRAN.
This is a major upgrade, with the following additional features:
* poisson family, with dense or sparse x
* Cox proportional hazards family, for dense x
* wide range of cross-validation features. All models have several criteria for cross-validation.
These include deviance, mean absolute error, misclassification error and "auc" for logistic or
2011 May 01
1
Different results of coefficients by packages penalized and glmnet
Dear R users:
Recently, I learn to use penalized logistic regression. Two packages
(penalized and glmnet) have the function of lasso.
So I write these code. However, I got different results of coef. Can someone
kindly explain.
# lasso using penalized
library(penalized)
pena.fit2<-penalized(HRLNM,penalized=~CN+NoSus,lambda1=1,model="logistic",standardize=TRUE)
pena.fit2
2010 Jun 02
2
glmnet strange error message
Hello fellow R users,
I have been getting a strange error message when using the cv.glmnet
function in the glmnet package. I am attempting to fit a multinomial
regression using the lasso. covars is a matrix with 80 rows and roughly 4000
columns, all the covariates are binary. resp is an eight level factor. I can
fit the model with no errors but when I try to cross-validate after about 30
seconds
2011 Feb 17
1
cv.glmnet errors
Hi,
I am trying to do multinomial regression using the glmnet package, but the
following gives me an error (for no reason apparent to me):
library(glmnet)
cv.glmnet(x=matrix(c(1,2,3,4,5,6,1,2,3,4,5,6),
nrow=6),y=as.factor(c(1,2,1,2,3,3)),family='multinomial',alpha=0.5,
nfolds=2)
The error i get is:
Error in if (outlist$msg != "Unknown error") return(outlist) :
argument is of
2013 Nov 12
1
GLMNET warning msg
Hi I'm getting the following warning msg after ?cv.glmnet and I'm wondering what it means...
dim(x) 10 12000;
dim(y) 10; #two groups case=1 and control=0
cv.glmnet(x, y)
Warning message:
Option grouped=FALSE enforced in cv.glmnet, since < 3 observations per fold
Thanks,
.kripa
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