print.clogitL1: Printing after fitting conditional logistic regression with...

In clogitL1: Fitting Exact Conditional Logistic Regression with Lasso and Elastic Net Penalties

Description

Takes a clogitL1 object and prints a summary of the sequence of models fitted.

Usage

 ## S3 method for class 'clogitL1'
 print(x, digits = 6, ...)

Arguments

x	an object of type clogitL1.
digits	the number of significant digits after the decimal to be printed
...	additional arguments to print function

Details

prints a 3 column data frame with columns:

• Df: number of non-zero parameters in model

• DevPerc: percentage of null deviance explained by current model

• Lambda: associated λ value

References

http://www.jstatsoft.org/v58/i12/

See Also

clogitL1

Examples

set.seed(145)

# data parameters
K = 10 # number of strata
n = 5 # number in strata
m = 2 # cases per stratum
p = 20 # predictors

# generate data
y = rep(c(rep(1, m), rep(0, n-m)), K)
X = matrix (rnorm(K*n*p, 0, 1), ncol = p) # pure noise
strata = sort(rep(1:K, n))

par(mfrow = c(1,2))
# fit the conditional logistic model
clObj = clogitL1(y=y, x=X, strata)
clObj

Example output

Loading required package: Rcpp
   Df  DevPerc   Lambda
1   0 0.000000 7.448607
2   1 0.022354 6.487466
3   1 0.039353 5.650347
4   2 0.063166 4.921246
5   2 0.087361 4.286226
6   2 0.106464 3.733147
7   2 0.121619 3.251435
8   2 0.133669 2.831882
9   4 0.147697 2.466466
10  7 0.169921 2.148202
11  9 0.195627 1.871006
12 10 0.222525 1.629578
13 11 0.247292 1.419303
14 15 0.277197 1.236161
15 15 0.316067 1.076651
16 15 0.348627 0.937724
17 15 0.376466 0.816724
18 16 0.400632 0.711336
19 18 0.428214 0.619548
20 18 0.455147 0.539604
21 19 0.479713 0.469975
22 19 0.504866 0.409331
23 19 0.528148 0.356513
24 19 0.550624 0.310510
25 19 0.573405 0.270443
26 19 0.598094 0.235546
27 19 0.627260 0.205152
28 19 0.662298 0.178680
29 19 0.702774 0.155623
30 19 0.745065 0.135542
31 19 0.784100 0.118052
32 19 0.817370 0.102819
33 19 0.845359 0.089552
34 20 0.868634 0.077996
35 20 0.888059 0.067932
36 20 0.904305 0.059166
37 20 0.917965 0.051532
38 20 0.929509 0.044882
39 20 0.939305 0.039091
40 20 0.947650 0.034047
41 20 0.954782 0.029653
42 20 0.960893 0.025827
43 20 0.966142 0.022494
44 20 0.970660 0.019592
45 20 0.974555 0.017064
46 20 0.977918 0.014862
47 20 0.980826 0.012944
48 20 0.983342 0.011274
49 20 0.985522 0.009819
50 20 0.987413 0.008552
51 20 0.989052 0.007449
52 20 0.990476 0.006487

clogitL1 documentation built on May 2, 2019, 3 p.m.