Package: ldt 0.5.3

ldt: Automated Uncertainty Analysis

Methods and tools for model selection and multi-model inference (Burnham and Anderson (2002) <doi:10.1007/b97636>, among others). 'SUR' (for parameter estimation), 'logit'/'probit' (for binary classification), and 'VARMA' (for time-series forecasting) are implemented. Evaluations are both in-sample and out-of-sample. It is designed to be efficient in terms of CPU usage and memory consumption.

Authors:Ramin Mojab [aut, cre], Stephen Becker [cph]

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ldt.pdf |ldt.html✨
ldt/json (API)
NEWS

# Install 'ldt' in R:
install.packages('ldt', repos = c('https://rmojab63.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/rmojab63/ldt/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • data.berka - Berka and Sochorova (1993) Dataset for Loan Default
  • data.pcp - IMF's Primary Commodity Prices
  • data.wdi - Long-run Growth from World Development Indicator Dataset

On CRAN:

3.18 score 7 scripts 252 downloads 38 exports 6 dependencies

Last updated 5 months agofrom:2b93f44eb2. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-win-x86_64OKNov 04 2024
R-4.5-linux-x86_64OKNov 04 2024
R-4.4-win-x86_64OKNov 04 2024
R-4.4-mac-x86_64OKNov 04 2024
R-4.4-mac-aarch64OKNov 04 2024
R-4.3-win-x86_64OKNov 04 2024
R-4.3-mac-x86_64OKNov 04 2024
R-4.3-mac-aarch64OKNov 04 2024

Exports:coefs.tableendogenousestim.binestim.surestim.varmaestim.varma.model.stringexogenousfan.plotget.combinationsget.dataget.options.lbfgsget.options.neldermeadget.options.newtonget.options.pcaget.options.rocget.search.itemsget.search.metricsget.search.modelchecksget.search.optionsget.varma.paramsrand.mnormals.cluster.hs.cluster.h.groups.combine.stats4s.distances.gld.density.quantiles.gld.from.momentss.gld.quantiles.metric.from.weights.pcas.rocs.weight.from.metricsearch.binsearch.sursearch.varmasim.binsim.sursim.varma

Dependencies:BHMASSrbibutilsRcppRdpacktdata

Binary Regression (loan default)

Rendered frombin.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2023-11-07
Started: 2023-07-04

SUR (longrun output growth)

Rendered fromsur.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2023-11-07
Started: 2023-07-04

VARMA (commodity prices)

Rendered fromvarma.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2023-11-07
Started: 2023-07-04

Readme and manuals

Help Manual

Help pageTopics
Adjust Indices in a Listadjust_indices_after_remove
Akaike Information CriterionAIC.ldt.estim
Bayesian Information CriterionBIC.ldt.estim
Box-Cox Transformation of Numeric MatrixboxCoxTransform
Extract Coefficients Matrixcoef.ldt.estim
Create Table of Coefficientscoefs.table
Combine a List of 'ldt.search' Objectscombine.search
Berka and Sochorova (1993) Dataset for Loan Defaultdata.berka
IMF's Primary Commodity Pricesdata.pcp
Long-run Growth from World Development Indicator Datasetdata.wdi
Extract Endogenous Variable(s) Dataendogenous
Convert a List of Equations to a MatrixeqList2Matrix
Estimate a Binary Choice Modelestim.bin
Get Model Nameestim.binary.model.string
Estimate a SUR Modelestim.sur
Estimate a VARMA Modelestim.varma
Get the Specification of an 'ldt.estim.varma' Modelestim.varma.model.string
Extract Exogenous Variable(s) Dataexogenous
Fan Plot Functionfan.plot
Extract Fitted Datafitted.ldt.estim
Define Combinations for Search Processget.combinations
Transform and Prepare Data for Analysisget.data
Append 'newX' to 'data$data' matrix.get.data.append.newX
Check if a column is discreteget.data.check.discrete
Check for an intercept in a matrixget.data.check.intercept
Remove Rows with Missing Observations from Dataget.data.keep.complete
Get Numeric Indices in a Combinationget.indexation
Get Options for L-BFGS Optimizationget.options.lbfgs
Options for Nelder-Mead Optimizationget.options.neldermead
Get Options for Newton Optimizationget.options.newton
Get Options for PCAget.options.pca
Get Options for ROC and AUC Calculationsget.options.roc
Specify the Purpose of the Model Search Processget.search.items
Get Options for Measuring Performanceget.search.metrics
Set Options to Exclude a Model Subsetget.search.modelchecks
Get Extra Options for Model Search Processget.search.options
Split VARMA parameter into its Componentsget.varma.params
Extract Maximum Log-LikelihoodlogLik.ldt.estim
Plot Diagnostics for 'ldt.estim' Objectplot.ldt.estim
Plot Predictions from a VARMA modelplot.ldt.varma.prediction
Extract Prediction Resultspredict.ldt.estim
Extract Prediction Results from a 'ldt.estim.varma' Objectpredict.ldt.estim.varma
Prints an 'ldt.estim' objectprint.ldt.estim
Prints an 'ldt.estim.projection' objectprint.ldt.estim.projection
Prints an 'ldt.list' objectprint.ldt.list
Prints an 'ldt.search' objectprint.ldt.search
Prints an 'ldt.varma.prediction' objectprint.ldt.varma.prediction
Generate Random Samples from a Multivariate Normal Distributionrand.mnormal
Extract Residuals Dataresiduals.ldt.estim
Hierarchical Clusterings.cluster.h
Group Variables with Hierarchical Clusterings.cluster.h.group
Combine Mean, Variance, Skewness, and Kurtosis This function combines two sets of mean, variance, skewness, and kurtosis and generates the combined statistics.s.combine.stats4
Get the Distances Between Variabless.distance
GLD Density-Quantile Functions.gld.density.quantile
Get the GLD Parameters from the momentss.gld.from.moments
GLD Quantile Functions.gld.quantile
Convert a Weight to Metrics.metric.from.weight
Principal Component Analysiss.pca
Get ROC Curve Data for Binary Classifications.roc
Convert a Metric to Weights.weight.from.metric
Create a Model Set for Binary Choice Modelssearch.bin
Create a Model Set for an R Functionsearch.rfunc
Step-wise estimationsearch.steps
Create a Model Set for SUR Modelssearch.sur
Create Model Set for VARMA Modelssearch.varma
Generate Random Sample from a DC Modelsim.bin
Generate Random Sample from an SUR Modelsim.sur
Generate Random Sample from a VARMA Modelsim.varma
Summary for an 'ldt.search' objectsummary.ldt.search
Summary for an 'ldt.search.item' objectsummary.ldt.search.item