Automated Uncertainty Analysis


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Documentation for package ‘ldt’ version 0.5.2

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adjust_indices_after_remove Adjust Indices in a List
AIC.ldt.estim Akaike Information Criterion
BIC.ldt.estim Bayesian Information Criterion
boxCoxTransform Box-Cox Transformation of Numeric Matrix
coef.ldt.estim Extract Coefficients Matrix
coefs.table Create Table of Coefficients
combine.search Combine a List of 'ldt.search' Objects
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
endogenous Extract Endogenous Variable(s) Data
eqList2Matrix Convert a List of Equations to a Matrix
estim.bin Estimate a Binary Choice Model
estim.binary.model.string Get Model Name
estim.sur Estimate a SUR Model
estim.varma Estimate a VARMA Model
estim.varma.model.string Get the Specification of an 'ldt.estim.varma' Model
exogenous Extract Exogenous Variable(s) Data
fan.plot Fan Plot Function
fitted.ldt.estim Extract Fitted Data
get.combinations Define Combinations for Search Process
get.data Transform and Prepare Data for Analysis
get.data.append.newX Append 'newX' to 'data$data' matrix.
get.data.check.discrete Check if a column is discrete
get.data.check.intercept Check for an intercept in a matrix
get.data.keep.complete Remove Rows with Missing Observations from Data
get.indexation Get Numeric Indices in a Combination
get.options.lbfgs Get Options for L-BFGS Optimization
get.options.neldermead Options for Nelder-Mead Optimization
get.options.newton Get Options for Newton Optimization
get.options.pca Get Options for PCA
get.options.roc Get Options for ROC and AUC Calculations
get.search.items Specify the Purpose of the Model Search Process
get.search.metrics Get Options for Measuring Performance
get.search.modelchecks Set Options to Exclude a Model Subset
get.search.options Get Extra Options for Model Search Process
get.varma.params Split VARMA parameter into its Components
logLik.ldt.estim Extract Maximum Log-Likelihood
plot.ldt.estim Plot Diagnostics for 'ldt.estim' Object
plot.ldt.varma.prediction Plot Predictions from a VARMA model
predict.ldt.estim Extract Prediction Results
predict.ldt.estim.varma Extract Prediction Results from a 'ldt.estim.varma' Object
print.ldt.estim Prints an 'ldt.estim' object
print.ldt.estim.projection Prints an 'ldt.estim.projection' object
print.ldt.list Prints an 'ldt.list' object
print.ldt.search Prints an 'ldt.search' object
print.ldt.varma.prediction Prints an 'ldt.varma.prediction' object
rand.mnormal Generate Random Samples from a Multivariate Normal Distribution
residuals.ldt.estim Extract Residuals Data
s.cluster.h Hierarchical Clustering
s.cluster.h.group Group Variables with Hierarchical Clustering
s.combine.stats4 Combine Mean, Variance, Skewness, and Kurtosis This function combines two sets of mean, variance, skewness, and kurtosis and generates the combined statistics.
s.distance Get the Distances Between Variables
s.gld.density.quantile GLD Density-Quantile Function
s.gld.from.moments Get the GLD Parameters from the moments
s.gld.quantile GLD Quantile Function
s.metric.from.weight Convert a Weight to Metric
s.pca Principal Component Analysis
s.roc Get ROC Curve Data for Binary Classification
s.weight.from.metric Convert a Metric to Weight
search.bin Create a Model Set for Binary Choice Models
search.rfunc Create a Model Set for an R Function
search.steps Step-wise estimation
search.sur Create a Model Set for SUR Models
search.varma Create Model Set for VARMA Models
sim.bin Generate Random Sample from a DC Model
sim.sur Generate Random Sample from an SUR Model
sim.varma Generate Random Sample from a VARMA Model
summary.ldt.search Summary for an 'ldt.search' object
summary.ldt.search.item Summary for an 'ldt.search.item' object