Description Usage Arguments Value Methods (by class) Author(s) References See Also Examples
nrm is used to fit multi-edge network regression models.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | nrm(
w,
adj,
xi = NULL,
pval = 0.01,
directed = TRUE,
selfloops = TRUE,
regular = FALSE,
...
)
## Default S3 method:
nrm(
w,
adj,
xi = NULL,
pval = 0.01,
directed = FALSE,
selfloops = FALSE,
regular = FALSE,
ci = TRUE,
significance = FALSE,
null = FALSE,
init = NULL,
...
)
## S3 method for class 'nrm'
print(x, suppressCall = FALSE, ...)
|
w |
an object of class |
adj |
matrix. The adjacency matrix of the response network (dependent variable). |
xi |
optional matrix. Passes a non-standard Ξ matrix. |
pval |
the significance level used to compute confidence intervals of the parameters. Per default, set to 0.01. |
directed |
logical. If |
selfloops |
logical. Whether selfloops are allowed. Default set to FALSE. |
regular |
logical. Whether the gHypEG regression should be performed
with correction of combinatorial effects ( |
... |
optional arguments to print or plot methods. |
ci |
logical. Whether to compute confidences for the parameters.
Defaults to |
significance |
logical. Whether to test the model significance against the null by means of lr-test. |
null |
logical. Is this a null model? Used for internal routines. |
init |
numeric. Vector of initial values used for numerical MLE. If only
a single value is passed, this is repeated to match the number of
predictors in |
x |
object of class |
suppressCall |
logical, indicating whether to print the call that generated x |
nrm returns an object of class 'nrm'.
The function summary is used to obtain and print a summary and analysis of the results. The generic accessory functions coefficients, etc, extract various useful features of the value returned by nrm.
An object of class 'nrm' is a list containing at least the following components:
coef |
a named vector of coefficients. |
confint |
a named matrix with confidence intervals and standard deviation for each coefficient. |
omega |
the estimated propensity matrix. |
xi
|
the matrix of possibilities. |
loglikelihood |
log-likelihood of the estimated model. |
AIC |
AIC of the estimated model. |
R2 |
Mc Fadden pseudo R-squared |
csR2 |
Cox and Snells pseudo R-squared |
significance |
the p-value of the likelihood-ratio test for the estimated model against the null. |
default
: Default method for nrm
nrm
: Print method for elements of class 'nrm'
.
Giona Casiraghi
Giona Casiraghi
Casiraghi, Giona. 'Multiplex Network Regression: How do relations drive interactions?.' arXiv preprint arXiv:1702.02048 (2017).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## For a complete example see the vignette
data('highschool.predictors')
highschool.m <- nrm(w=highschool.predictors[1], adj=contacts.adj, directed=FALSE,
selfloops=FALSE)
highschool.m
data('highschool.predictors')
highschool.m <- nrm(w=highschool.predictors, adj=contacts.adj, directed=FALSE,
selfloops=FALSE)
highschool.m
|
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