From 36123fd4c8229ef8ae25b258a30a37670502dcd6 Mon Sep 17 00:00:00 2001 From: Mahendra Mariadassou Date: Tue, 20 Feb 2024 17:56:42 +0100 Subject: [PATCH] Update doc --- man/Networkfamily.Rd | 30 ++++++++++++++++++------------ man/PLNnetwork.Rd | 7 ++++--- man/PLNnetwork_param.Rd | 4 ++-- man/PLNnetworkfamily.Rd | 10 ++++++---- man/ZIPLN_param.Rd | 13 ++++++------- man/ZIPLNfit.Rd | 6 +++++- man/ZIPLNfit_diagonal.Rd | 2 +- man/ZIPLNfit_fixed.Rd | 2 +- man/ZIPLNfit_sparse.Rd | 4 ++-- man/ZIPLNfit_spherical.Rd | 2 +- man/ZIPLNnetwork.Rd | 7 ++++--- man/ZIPLNnetwork_param.Rd | 12 ++++++------ man/ZIPLNnetworkfamily.Rd | 2 +- man/coefficient_path.Rd | 2 +- man/plot.Networkfamily.Rd | 7 ++++--- man/plot.ZIPLNfit_sparse.Rd | 2 +- man/stability_selection.Rd | 6 +++--- 17 files changed, 66 insertions(+), 52 deletions(-) diff --git a/man/Networkfamily.Rd b/man/Networkfamily.Rd index f8d9df87..48bd6116 100644 --- a/man/Networkfamily.Rd +++ b/man/Networkfamily.Rd @@ -2,16 +2,18 @@ % Please edit documentation in R/PLNnetworkfamily-class.R \name{Networkfamily} \alias{Networkfamily} -\title{An R6 Class to virtually represent a collection of Networkfit (either standard PLN or ZI-PLN)} +\title{An R6 Class to virtually represent a collection of network fits} \description{ -The function \code{\link[=PLNnetwork]{PLNnetwork()}} produces an instance of this class. +The functions \code{\link[=PLNnetwork]{PLNnetwork()}} and \code{\link[=ZIPLNnetwork]{ZIPLNnetwork()}} both produce an instance of this class, which can be thought of as a vector of \code{\link{PLNnetworkfit}}s \code{\link{ZIPLNnetworkfit}}s (indexed by penalty parameter) -This class comes with a set of methods, some of them being useful for the user: +This class comes with a set of methods mostly used to compare +network fits (in terms of goodness of fit) or extract one from +the family (based on penalty parameter and/or goodness of it). See the documentation for \code{\link[=getBestModel]{getBestModel()}}, -\code{\link[=getModel]{getModel()}} and \link[=plot.PLNnetworkfamily]{plot()} +\code{\link[=getModel]{getModel()}} and \link[=plot.Networkfamily]{plot()} for the user-facing ones. } \seealso{ -The function \code{\link[=PLNnetwork]{PLNnetwork()}}, the class \code{\link{PLNnetworkfit}} +The functions \code{\link[=PLNnetwork]{PLNnetwork()}}, \code{\link[=ZIPLNnetwork]{ZIPLNnetwork()}} and the classes \code{\link{PLNnetworkfit}}, \code{\link{ZIPLNnetworkfit}} } \section{Super class}{ \code{\link[PLNmodels:PLNfamily]{PLNmodels::PLNfamily}} -> \code{Networkfamily} @@ -25,7 +27,7 @@ The function \code{\link[=PLNnetwork]{PLNnetwork()}}, the class \code{\link{PLNn \item{\code{stability}}{mean edge stability along the penalty path} -\item{\code{criteria}}{a data frame with the values of some criteria (approximated log-likelihood, (E)BIC, ICL and R2, stability) for the collection of models / fits +\item{\code{criteria}}{a data frame with the values of some criteria (variational log-likelihood, (E)BIC, ICL and R2, stability) for the collection of models / fits BIC, ICL and EBIC are defined so that they are on the same scale as the model log-likelihood, i.e. with the form, loglik - 0.5 penalty} } \if{html}{\out{}} @@ -74,7 +76,7 @@ Initialize all models in the collection \if{html}{\out{}} } \subsection{Returns}{ -Update current \code{\link{PLNnetworkfit}} with smart starting values +Update all network fits in the family with smart starting values } } \if{html}{\out{
}} @@ -100,7 +102,7 @@ Call to the C++ optimizer on all models of the collection \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-Networkfamily-coefficient_path}{}}} \subsection{Method \code{coefficient_path()}}{ -Extract the regularization path of a \code{\link{PLNnetworkfamily}} +Extract the regularization path of a \code{\link{Networkfamily}} \subsection{Usage}{ \if{html}{\out{
}}\preformatted{Networkfamily$coefficient_path(precision = TRUE, corr = TRUE)}\if{html}{\out{
}} } @@ -127,18 +129,22 @@ Extract the best network in the family according to some criteria \subsection{Arguments}{ \if{html}{\out{
}} \describe{ -\item{\code{crit}}{character. Criterion used to perform the selection. Is "StARS" is chosen but \verb{$stability} field is empty, will compute stability path.} +\item{\code{crit}}{character. Criterion used to perform the selection. If "StARS" is chosen but \verb{$stability} field is empty, will compute stability path.} \item{\code{stability}}{Only used for "StARS" criterion. A scalar indicating the target stability (= 1 - 2 beta) at which the network is selected. Default is \code{0.9}.} } \if{html}{\out{
}} } +\subsection{Details}{ +For BIC and EBIC criteria, higher is better. +} + } \if{html}{\out{
}} \if{html}{\out{}} \if{latex}{\out{\hypertarget{method-Networkfamily-plot}{}}} \subsection{Method \code{plot()}}{ -Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of PLNnetwork fits (a \code{\link{PLNnetworkfamily}}) +Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of network fits (a \code{\link{Networkfamily}}) \subsection{Usage}{ \if{html}{\out{
}}\preformatted{Networkfamily$plot( criteria = c("loglik", "pen_loglik", "BIC", "EBIC"), @@ -154,7 +160,7 @@ Display various outputs (goodness-of-fit criteria, robustness, diagnostic) assoc \item{\code{reverse}}{A logical indicating whether to plot the value of the criteria in the "natural" direction (loglik - 0.5 penalty) or in the "reverse" direction (-2 loglik + penalty). Default to FALSE, i.e use the -natural direction, on the same scale as the log-likelihood..} +natural direction, on the same scale as the log-likelihood.} \item{\code{log.x}}{logical: should the x-axis be represented in log-scale? Default is \code{TRUE}.} } @@ -176,7 +182,7 @@ Plot stability path \subsection{Arguments}{ \if{html}{\out{
}} \describe{ -\item{\code{stability}}{scalar: the targeted level of stability in stability plot. Default is \code{0.9}.} +\item{\code{stability}}{scalar: the targeted level of stability using stability selection. Default is \code{0.9}.} \item{\code{log.x}}{logical: should the x-axis be represented in log-scale? Default is \code{TRUE}.} } diff --git a/man/PLNnetwork.Rd b/man/PLNnetwork.Rd index 36184572..51589dfe 100644 --- a/man/PLNnetwork.Rd +++ b/man/PLNnetwork.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/PLNnetwork.R \name{PLNnetwork} \alias{PLNnetwork} -\title{Poisson lognormal model towards sparse network inference} +\title{Sparse Poisson lognormal model for network inference} \usage{ PLNnetwork( formula, @@ -31,8 +31,9 @@ an R6 object with class \code{\link{PLNnetworkfamily}}, which contains a collection of models with class \code{\link{PLNnetworkfit}} } \description{ -Fit the sparse inverse covariance variant of the Poisson lognormal with a variational algorithm -for a collection of sparsity parameter values distributed on a log scale. Use the (g)lm syntax for model specification (covariates, offsets). +Perform sparse inverse covariance estimation for the Zero Inflated Poisson lognormal model +using a variational algorithm. Iterate over a range of logarithmically spaced sparsity parameter values. +Use the (g)lm syntax to specify the model (including covariates and offsets). } \examples{ data(trichoptera) diff --git a/man/PLNnetwork_param.Rd b/man/PLNnetwork_param.Rd index f74ea009..c40c1350 100644 --- a/man/PLNnetwork_param.Rd +++ b/man/PLNnetwork_param.Rd @@ -30,7 +30,7 @@ PLNnetwork_param( \item{penalize_diagonal}{boolean: should the diagonal terms be penalized in the graphical-Lasso? Default is \code{TRUE}} -\item{penalty_weights}{either a single or a list of p x p matrix of weights (default filled with 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values.} +\item{penalty_weights}{either a single or a list of p x p matrix of weights (default: all weights equal to 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values.} \item{config_post}{a list for controlling the post-treatment (optional bootstrap, jackknife, R2, etc).} @@ -49,7 +49,7 @@ Helper to define list of parameters to control the PLN fit. All arguments have d \details{ See \code{\link[=PLN_param]{PLN_param()}} for a full description of the generic optimization parameters. PLNnetwork_param() also has two additional parameters controlling the optimization due the inner-outer loop structure of the optimizer: \itemize{ -\item "ftol_out" outer solver stops when an optimization step changes the objective function by less than xtol multiplied by the absolute value of the parameter. Default is 1e-6 +\item "ftol_out" outer solver stops when an optimization step changes the objective function by less than ftol multiplied by the absolute value of the parameter. Default is 1e-6 \item "maxit_out" outer solver stops when the number of iteration exceeds maxit_out. Default is 50 } } diff --git a/man/PLNnetworkfamily.Rd b/man/PLNnetworkfamily.Rd index 6490ced9..6cb3e9ab 100644 --- a/man/PLNnetworkfamily.Rd +++ b/man/PLNnetworkfamily.Rd @@ -2,13 +2,15 @@ % Please edit documentation in R/PLNnetworkfamily-class.R \name{PLNnetworkfamily} \alias{PLNnetworkfamily} -\title{An R6 Class to represent a collection of PLNnetworkfit} +\title{An R6 Class to represent a collection of \code{\link{PLNnetworkfit}}s} \description{ The function \code{\link[=PLNnetwork]{PLNnetwork()}} produces an instance of this class. -This class comes with a set of methods, some of them being useful for the user: +This class comes with a set of methods mostly used to compare +network fits (in terms of goodness of fit) or extract one from +the family (based on penalty parameter and/or goodness of it). See the documentation for \code{\link[=getBestModel]{getBestModel()}}, -\code{\link[=getModel]{getModel()}} and \link[=plot.PLNnetworkfamily]{plot()} +\code{\link[=getModel]{getModel()}} and \link[=plot.Networkfamily]{plot()} for the user-facing ones. } \examples{ data(trichoptera) @@ -87,7 +89,7 @@ Compute the stability path by stability selection \describe{ \item{\code{subsamples}}{a list of vectors describing the subsamples. The number of vectors (or list length) determines the number of subsamples used in the stability selection. Automatically set to 20 subsamples with size \code{10*sqrt(n)} if \code{n >= 144} and \code{0.8*n} otherwise following Liu et al. (2010) recommendations.} -\item{\code{control}}{a list controlling the main optimization process in each call to PLNnetwork. See \code{\link[=PLNnetwork]{PLNnetwork()}} for details.} +\item{\code{control}}{a list controlling the main optimization process in each call to \code{\link[=PLNnetwork]{PLNnetwork()}}. See \code{\link[=PLNnetwork]{PLNnetwork()}} and \code{\link[=PLN_param]{PLN_param()}} for details.} } \if{html}{\out{
}} } diff --git a/man/ZIPLN_param.Rd b/man/ZIPLN_param.Rd index 13d6fb2e..5d9a624d 100644 --- a/man/ZIPLN_param.Rd +++ b/man/ZIPLN_param.Rd @@ -28,9 +28,9 @@ ZIPLN_param( \item{penalty}{a user-defined penalty to sparsify the residual covariance. Defaults to 0 (no sparsity).} -\item{penalize_diagonal}{boolean: should the diagonal terms be penalized in the graphical-Lasso? Only relevant with sparse covariance. Default is \code{TRUE}} +\item{penalize_diagonal}{boolean: should the diagonal terms be penalized in the graphical-Lasso? Default is \code{TRUE}} -\item{penalty_weights}{p x p matrix of weights (default filled with 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values. Only relevant with sparse covariance.} +\item{penalty_weights}{either a single or a list of p x p matrix of weights (default: all weights equal to 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values.} \item{config_post}{a list for controlling the post-treatments (optional bootstrap, jackknife, R2, etc.). See details} @@ -47,12 +47,11 @@ list of parameters used during the fit and post-processing steps Helper to define list of parameters to control the PLN fit. All arguments have defaults. } \details{ -See \code{\link[=PLN_param]{PLN_param()}} for a full description of the generic optimization parameters. ZIPLN_param() also -has two additional parameters controlling the optimization due the inner-outer loop structure of the optimizer, -and additional parameter controlling the form of the variational approximation of the zero inflation: +See \code{\link[=PLN_param]{PLN_param()}} and \code{\link[=PLNnetwork_param]{PLNnetwork_param()}} for a full description of the generic optimization parameters. Like \code{\link[=PLNnetwork_param]{PLNnetwork_param()}}, ZIPLN_param() has two parameters controlling the optimization due the inner-outer loop structure of the optimizer: \itemize{ -\item "ftol_out" outer solver stops when an optimization step changes the objective function by less than \code{ftol_out} multiplied by the absolute value of the parameter. Default is 1e-8 +\item "ftol_out" outer solver stops when an optimization step changes the objective function by less than \code{ftol_out} multiplied by the absolute value of the parameter. Default is 1e-6 \item "maxit_out" outer solver stops when the number of iteration exceeds \code{maxit_out}. Default is 100 -\item "approx_ZI" either use an exact or approximated conditional distribution for the zero inflantion. Default is FALSE +and one additional parameter controlling the form of the variational approximation of the zero inflation: +\item "approx_ZI" either uses an exact or approximated conditional distribution for the zero inflation. Default is FALSE } } diff --git a/man/ZIPLNfit.Rd b/man/ZIPLNfit.Rd index e8411b90..5d4a5950 100644 --- a/man/ZIPLNfit.Rd +++ b/man/ZIPLNfit.Rd @@ -40,7 +40,11 @@ print(myPLN) \item{\code{d0}}{number of covariates in the ZI part} -\item{\code{nb_param}}{number of parameters in the current PLN model} +\item{\code{nb_param_zi}}{number of parameters in the ZI part of the model} + +\item{\code{nb_param_pln}}{number of parameters in the PLN part of the model} + +\item{\code{nb_param}}{number of parameters in the ZIPLN model} \item{\code{model_par}}{a list with the matrices of parameters found in the model (B, Sigma, plus some others depending on the variant)} diff --git a/man/ZIPLNfit_diagonal.Rd b/man/ZIPLNfit_diagonal.Rd index 7c076442..8b75204f 100644 --- a/man/ZIPLNfit_diagonal.Rd +++ b/man/ZIPLNfit_diagonal.Rd @@ -24,7 +24,7 @@ print(myPLN) \section{Active bindings}{ \if{html}{\out{
}} \describe{ -\item{\code{nb_param}}{number of parameters in the current PLN model} +\item{\code{nb_param_pln}}{number of parameters in the PLN part of the current model} \item{\code{vcov_model}}{character: the model used for the residual covariance} } diff --git a/man/ZIPLNfit_fixed.Rd b/man/ZIPLNfit_fixed.Rd index 6f0ba648..6f6da2fd 100644 --- a/man/ZIPLNfit_fixed.Rd +++ b/man/ZIPLNfit_fixed.Rd @@ -25,7 +25,7 @@ print(myPLN) \section{Active bindings}{ \if{html}{\out{
}} \describe{ -\item{\code{nb_param}}{number of parameters in the current PLN model} +\item{\code{nb_param_pln}}{number of parameters in the PLN part of the current model} \item{\code{vcov_model}}{character: the model used for the residual covariance} } diff --git a/man/ZIPLNfit_sparse.Rd b/man/ZIPLNfit_sparse.Rd index 46dd2d39..f5e5387e 100644 --- a/man/ZIPLNfit_sparse.Rd +++ b/man/ZIPLNfit_sparse.Rd @@ -31,7 +31,7 @@ plot(myPLN) \item{\code{n_edges}}{number of edges if the network (non null coefficient of the sparse precision matrix)} -\item{\code{nb_param}}{number of parameters in the current PLN model} +\item{\code{nb_param_pln}}{number of parameters in the PLN part of the current model} \item{\code{vcov_model}}{character: the model used for the residual covariance} @@ -102,7 +102,7 @@ Extract interaction network in the latent space \if{html}{\out{
}} } \subsection{Returns}{ -a square matrix of size \code{PLNnetworkfit$n} +a square matrix of size \code{ZIPLNfit_sparse$n} } } \if{html}{\out{
}} diff --git a/man/ZIPLNfit_spherical.Rd b/man/ZIPLNfit_spherical.Rd index 4548dade..5779c2c8 100644 --- a/man/ZIPLNfit_spherical.Rd +++ b/man/ZIPLNfit_spherical.Rd @@ -24,7 +24,7 @@ print(myPLN) \section{Active bindings}{ \if{html}{\out{
}} \describe{ -\item{\code{nb_param}}{number of parameters in the current PLN model} +\item{\code{nb_param_pln}}{number of parameters in the PLN part of the current model} \item{\code{vcov_model}}{character: the model used for the residual covariance} } diff --git a/man/ZIPLNnetwork.Rd b/man/ZIPLNnetwork.Rd index de38ed41..aef11b01 100644 --- a/man/ZIPLNnetwork.Rd +++ b/man/ZIPLNnetwork.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/ZIPLNnetwork.R \name{ZIPLNnetwork} \alias{ZIPLNnetwork} -\title{Zero Inflated Poisson lognormal model toward sparse network inference} +\title{Zero Inflated Sparse Poisson lognormal model for network inference} \usage{ ZIPLNnetwork( formula, @@ -40,8 +40,9 @@ for details.} an R6 object with class \code{\link{ZIPLNnetworkfamily}} } \description{ -Fit the sparse inverse covariance variant of the Zero Inflated Poisson lognormal with a variational algorithm -for a collection of sparsity parameter values distributed on a log scale. Use the (g)lm syntax for model specification (covariates, offsets). +Perform sparse inverse covariance estimation for the Zero Inflated Poisson lognormal model +using a variational algorithm. Iterate over a range of logarithmically spaced sparsity parameter values. +Use the (g)lm syntax to specify the model (including covariates and offsets). } \details{ Covariates for the Zero-Inflation parameter (using a logistic regression model) can be specified in the formula RHS using the pipe diff --git a/man/ZIPLNnetwork_param.Rd b/man/ZIPLNnetwork_param.Rd index 7b9db861..fe3d4daa 100644 --- a/man/ZIPLNnetwork_param.Rd +++ b/man/ZIPLNnetwork_param.Rd @@ -30,7 +30,7 @@ ZIPLNnetwork_param( \item{penalize_diagonal}{boolean: should the diagonal terms be penalized in the graphical-Lasso? Default is \code{TRUE}} -\item{penalty_weights}{either a single or a list of p x p matrix of weights (default filled with 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values.} +\item{penalty_weights}{either a single or a list of p x p matrix of weights (default: all weights equal to 1) to adapt the amount of shrinkage to each pairs of node. Must be symmetric with positive values.} \item{config_post}{a list for controlling the post-treatment (optional bootstrap, jackknife, R2, etc).} @@ -44,15 +44,15 @@ which sometimes speeds up the inference.} list of parameters configuring the fit. } \description{ -Helper to define list of parameters to control the PLN fit. All arguments have defaults. +Helper to define list of parameters to control the ZIPLNnetwork fit. All arguments have defaults. } \details{ -See \code{\link[=PLN_param]{PLN_param()}} for a full description of the generic optimization parameters. PLNnetwork_param() also has two additional parameters controlling the optimization due the inner-outer loop structure of the optimizer: +See \code{\link[=PLNnetwork_param]{PLNnetwork_param()}} for a full description of the optimization parameters. Note that some defaults values are different than those used in \code{\link[=PLNnetwork_param]{PLNnetwork_param()}}: \itemize{ -\item "ftol_out" outer solver stops when an optimization step changes the objective function by less than xtol multiplied by the absolute value of the parameter. Default is 1e-6 -\item "maxit_out" outer solver stops when the number of iteration exceeds maxit_out. Default is 50 +\item "ftol_out" (outer loop convergence tolerance the objective function) is set by default to 1e-6 +\item "maxit_out" (max number of iterations for the outer loop) is set by default to 100 } } \seealso{ -\code{\link[=PLN_param]{PLN_param()}} +\code{\link[=PLNnetwork_param]{PLNnetwork_param()}} and \code{\link[=PLN_param]{PLN_param()}} } diff --git a/man/ZIPLNnetworkfamily.Rd b/man/ZIPLNnetworkfamily.Rd index 19b4e49d..0bf90623 100644 --- a/man/ZIPLNnetworkfamily.Rd +++ b/man/ZIPLNnetworkfamily.Rd @@ -94,7 +94,7 @@ Compute the stability path by stability selection \describe{ \item{\code{subsamples}}{a list of vectors describing the subsamples. The number of vectors (or list length) determines the number of subsamples used in the stability selection. Automatically set to 20 subsamples with size \code{10*sqrt(n)} if \code{n >= 144} and \code{0.8*n} otherwise following Liu et al. (2010) recommendations.} -\item{\code{control}}{a list controlling the main optimization process in each call to PLNnetwork. See \code{\link[=PLNnetwork]{PLNnetwork()}} for details.} +\item{\code{control}}{a list controlling the main optimization process in each call to \code{\link[=PLNnetwork]{PLNnetwork()}}. See \code{\link[=ZIPLNnetwork]{ZIPLNnetwork()}} and \code{\link[=ZIPLN_param]{ZIPLN_param()}} for details.} } \if{html}{\out{
}} } diff --git a/man/coefficient_path.Rd b/man/coefficient_path.Rd index 3a389ccb..45552555 100644 --- a/man/coefficient_path.Rd +++ b/man/coefficient_path.Rd @@ -7,7 +7,7 @@ coefficient_path(Robject, precision = TRUE, corr = TRUE) } \arguments{ -\item{Robject}{an object with class \code{\link{PLNnetworkfamily}}, i.e. an output from \code{\link[=PLNnetwork]{PLNnetwork()}}} +\item{Robject}{an object with class \code{\link{Networkfamily}}, i.e. an output from \code{\link[=PLNnetwork]{PLNnetwork()}}} \item{precision}{a logical, should the coefficients of the precision matrix Omega or the covariance matrix Sigma be sent back. Default is \code{TRUE}.} diff --git a/man/plot.Networkfamily.Rd b/man/plot.Networkfamily.Rd index b54595d7..ab24d8b7 100644 --- a/man/plot.Networkfamily.Rd +++ b/man/plot.Networkfamily.Rd @@ -37,12 +37,13 @@ ) } \arguments{ -\item{x}{an R6 object with class \code{\link{PLNnetworkfamily}}} +\item{x}{an R6 object with class \code{\link{PLNnetworkfamily}} or \code{\link{ZIPLNnetworkfamily}}} \item{type}{a character, either "criteria", "stability" or "diagnostic" for the type of plot.} -\item{criteria}{vector of characters. The criteria to plot in c("loglik", "BIC", "ICL", "R_squared", "EBIC", "pen_loglik"). -Default is c("loglik", "pen_loglik", "BIC", "EBIC"). Only relevant when \code{type = "criteria"}.} +\item{criteria}{Vector of criteria to plot, to be selected among "loglik" (log-likelihood), +"BIC", "ICL", "R_squared", "EBIC" and "pen_loglik" (penalized log-likelihood). +Default is c("loglik", "pen_loglik", "BIC", "EBIC"). Only used when \code{type = "criteria"}.} \item{reverse}{A logical indicating whether to plot the value of the criteria in the "natural" direction (loglik - 0.5 penalty) or in the "reverse" direction (-2 loglik + penalty). Default to FALSE, i.e use the diff --git a/man/plot.ZIPLNfit_sparse.Rd b/man/plot.ZIPLNfit_sparse.Rd index 52dad7c2..d358717c 100644 --- a/man/plot.ZIPLNfit_sparse.Rd +++ b/man/plot.ZIPLNfit_sparse.Rd @@ -17,7 +17,7 @@ ) } \arguments{ -\item{x}{an R6 object with class \code{\link{PLNnetworkfit}}} +\item{x}{an R6 object with class \code{\link{ZIPLNfit_sparse}}} \item{type}{character. Value of the weight of the edges in the network, either "partial_cor" (partial correlation) or "support" (binary). Default is \code{"partial_cor"}.} diff --git a/man/stability_selection.Rd b/man/stability_selection.Rd index 2fb5384a..ae378f80 100644 --- a/man/stability_selection.Rd +++ b/man/stability_selection.Rd @@ -12,16 +12,16 @@ stability_selection( ) } \arguments{ -\item{Robject}{an object with class \code{\link{PLNnetworkfamily}}, i.e. an output from \code{\link[=PLNnetwork]{PLNnetwork()}}} +\item{Robject}{an object with class \code{\link{PLNnetworkfamily}} or \code{\link{ZIPLNnetworkfamily}}, i.e. an output from \code{\link[=PLNnetwork]{PLNnetwork()}} or \code{\link[=ZIPLNnetwork]{ZIPLNnetwork()}}} \item{subsamples}{a list of vectors describing the subsamples. The number of vectors (or list length) determines th number of subsamples used in the stability selection. Automatically set to 20 subsamples with size \code{10*sqrt(n)} if \code{n >= 144} and \code{0.8*n} otherwise following Liu et al. (2010) recommendations.} -\item{control}{a list controlling the main optimization process in each call to PLNnetwork. See \code{\link[=PLNnetwork]{PLNnetwork()}} for details.} +\item{control}{a list controlling the main optimization process in each call to \code{\link[=PLNnetwork]{PLNnetwork()}} or \code{\link[=ZIPLNnetwork]{ZIPLNnetwork()}}. See \code{\link[=PLN_param]{PLN_param()}} or \code{\link[=ZIPLN_param]{ZIPLN_param()}} for details.} \item{force}{force computation of the stability path, even if a previous one has been detected.} } \value{ -the list of subsamples. The estimated probabilities of selection of the edges are stored in the fields \code{stability_path} of the initial Robject with class \code{\link{PLNnetworkfamily}} +the list of subsamples. The estimated probabilities of selection of the edges are stored in the fields \code{stability_path} of the initial Robject with class \code{\link{Networkfamily}} } \description{ This function computes the StARS stability criteria over a path of penalties. If a path has already been computed, the functions stops with a message unless \code{force = TRUE} has been specified.