Lagrangian Multiplier Smoothing Splines for Smooth Function Estimation

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Documentation for package ‘lgspline’ version 0.1.0

• DESCRIPTION file.

Help Pages

%**%	Efficient Matrix Multiplication Operator
coef.lgspline	Extract model coefficients
create_onehot	Create One-Hot Encoded Matrix
Details	Lagrangian Multiplier Smoothing Splines: Mathematical Details
find_extremum	Find Extremum of Fitted Lagrangian Multiplier Smoothing Spline
generate_posterior	Generate Posterior Samples from Fitted Lagrangian Multiplier Smoothing Spline
leave_one_out	Compute Leave-One-Out Cross-Validated predictions for Gaussian Response/Identity Link under Constraint.
lgspline	Fit Lagrangian Multiplier Smoothing Splines
loglik_weibull	Compute Log-Likelihood for Weibull Accelerated Failure Time Model
matinvsqrt	Calculate Matrix Inverse Square Root
matsqrt	Calculate Matrix Square Root
plot.lgspline	Plot Method for Lagrangian Multiplier Smoothing Spline Models
predict.lgspline	Predict Method for Fitted Lagrangian Multiplier Smoothing Spline
print.lgspline	Print Method for lgspline Objects
print.summary.lgspline	Print Method for lgspline Object Summaries
prior_loglik	Log-Prior Distribution Evaluation for lgspline Models
summary.lgspline	Summary method for lgspline Objects
wald_univariate	Univariate Wald Tests and Confidence Intervals for Lagrangian Multiplier Smoothing Splines
weibull_dispersion_function	Estimate Weibull Dispersion for Accelerated Failure Time Model
weibull_family	Weibull Family for Survival Model Specification
weibull_glm_weight_function	Weibull GLM Weight Function for Constructing Information Matrix
weibull_qp_score_function	Compute gradient of log-likelihood of Weibull accelerated failure model without penalization
weibull_scale	Estimate Scale for Weibull Accelerated Failure Time Model
weibull_shur_correction	Correction for the Variance-Covariance Matrix for Uncertainty in Scale