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Infusion (version 2.2.0)

Inference Using Simulation

Description

Implements functions for simulation-based inference. In particular, implements functions to perform likelihood inference from data summaries whose distributions are simulated. The package implements more advanced methods than the ones first described in: Rousset, Gouy, Almoyna and Courtiol (2017) .

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Version

Install

install.packages('Infusion')

Monthly Downloads

808

Version

2.2.0

License

CeCILL-2

Maintainer

Franois Rousset

Last Published

September 26th, 2024

Functions in Infusion (2.2.0)

check_raw_stats

Check linear dependencies among raw summary statistics
get_from

Backward-compatible extractor from summary-likelihood objects
focal_refine

Refine summary likelihood profile in focal parameter values
densv

Saved computations of inferred log-likelihoods
example_reftable

Workflow for method with reference table
extractors

Summary, print and logLik methods for Infusion results.
dMixmod

Internal S4 classes.
example_raw_proj

Workflow for primitive method, with projections
get_nbCluster_range

Control of number of components in Gaussian mixture modelling
get_workflow_design

Workflow design
example_raw

Workflow for primitive method, without projections
declare_latent

Modeling and predicting latent variables
multi_binning

Multivariate histogram
infer_surface

Infer a (summary) likelihood or tail probability surface from inferred likelihoods
init_reftable

Define starting points in parameter space.
goftest

Assessing goodness of fit of inference using simulation
handling_NAs

Discrete probability masses and NA/NaN/Inf in distributions of summary statistics.
plot_proj

Diagnostic plots for projections
plot1Dprof

Plot likelihood profiles
infer_SLik_joint

Infer a (summary) likelihood surface from a simulation table
profile.SLik

Compute profile summary likelihood
predict.SLik_j

Evaluate log-likelihood for given parameters
infer_logLs

Infer log Likelihoods using simulated distributions of summary statistics
summLik

Model density evaluation for given data and parameters
.update_obs

Updating an 'SLik_j' object for new data
rparam

Sample the parameter space
reparam_fit

Conversion to new parameter spaces
simulate.SLik_j

Simulate method for an SLik_j object.
save_MAFs

Save or load MAF Python objects
options

Infusion options settings
plot.SLik

Plot SLik or SLikp objects
refine

Refine estimates iteratively
project.character

Learn a projection method for statistics and apply it
confint.SLik

Compute confidence intervals by (profile) summary likelihood
Infusion-internal

Internal Infusion Functions
get_LRboot

Summary likelihood ratio tests
MAF.options

Control of MAF design and training
add_simulation

Create or augment a list of simulated distributions of summary statistics
Infusion

Inference using simulation
constr_crits

Specificying arbitrary constraints on parameters
add_reftable

Create or augment a list of simulated distributions of summary statistics
MSL

Maximum likelihood from an inferred likelihood surface