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 |