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vasicekreg 1.3.0 (2026-09-20)

Datasets

• Added please_microbiome, a long-format data frame of genus-level relative abundances from the pediatric study of Lewis et al. (2015), reconstructed from the public chvlyl/PLEASE repository following the filtering and recoding conventions of the ZIBR R package (Chen and Li, 2016, https://CRAN.R-project.org/package=ZIBR). The data cover 3186 post-baseline observations from 59 subjects (47 anti-TNF, 12 EEN) and 18 bacterial genera, with the week-0 abundance of each genus stored as a subject-level covariate. The dataset is documented in R/please_microbiome.R and reproduced by data-raw/please_microbiome.R.

Longitudinal two-part mixed models

• Reject simultaneous formula and legacy arguments for either component or for the subject grouping variable, with explicit error messages.

• Removed the unused internal model_name argument and the redundant NA in the random-effect boundary check.

• Clarified that separate component optimization maximizes the joint likelihood under independent random effects and no shared parameters.

• Removed installation and export checks for the package itself from zavr(). The positive density now calls dNVASIM() directly, and dependency checks and version reporting cover external packages only.

• Standardized longitudinal fixed-effect notation as gamma for the discrete component and beta for the continuous component. Renamed the discrete coefficient prefix from alpha_ to gamma_ in coef() and vcov() and aligned printed headings and documentation. Code that selects discrete coefficients by name must use gamma_.

• Added zavr(), a zero-augmented normal-kernel Vasicek regression for longitudinal responses in [0, 1). A logistic component models presence, a Vasicek component models the conditional mean of positive responses, and each component has an independent subject-specific Gaussian random intercept.

• Added zabr(), a zero-augmented beta random-intercept model following Chen and Li (2016), to provide a directly comparable beta positive component under the same computational interface.

• Added one-sided formula interfaces for the presence and positive components and a random = ~ 1 | subject interface. The earlier character-vector arguments remain temporarily available with deprecation warnings.

• Added non-adaptive Gauss–Hermite integration, multiple starting values, component-wise and joint likelihood-ratio tests, Hessian-based covariance estimates, optimization diagnostics, and print(), coef(), vcov(), logLik(), nobs(), and BIC() methods.

• Joint AIC and BIC are calculated from the complete two-part likelihood. BIC uses the number of subjects in its penalty, following the PROC NLMIXED convention. Component-wise criteria are retained as diagnostics: AIC values are additive, whereas BIC values are not generally additive because the positive component uses only subjects with at least one positive response.

• Added documentation, references, examples, dependency declarations, S3 registrations, and integration tests for the new longitudinal interfaces.

vasicekreg 1.2.0 (2026-09-03)

Self-contained quantile families

• Renamed the fixed quantile-level argument from tau to quantile in NVASIQ, LVASIQ, and HVASIQ, including their d, p, q, and r functions and compiled interfaces.
• Removed the dependency of the three quantile-family constructors on a global tau object. The fixed level is now passed directly, for example as NVASIQ(quantile = 0.25), stored in the family definition, and embedded as a numeric literal in the derivative, deviance, initial-value, residual, and conditional-moment components of the family object.
• Updated vasicek_envelope() to recover the fixed level from the fitted model and use it in bootstrap simulation and refitting. Models fitted at different quantile levels can therefore coexist safely in one session.
• Added tests for independence from global variables, simultaneous fits at different levels, serialization, automatic refitting, and fixed-level envelope simulation.
• Retained tau unchanged as the estimated conditional probability at one among nonzero observations in ZOANVASIM.

Interface and documentation review

• Added an application-oriented vignette, replacing the obsolete draft and covering all four included data sets. It fits the five bodyfat responses, compares the three quantile kernels, illustrates the zero-, one-, and zero-and-one-augmented families with transport, trees, and aep, and documents conditional and marginal fitted quantities and simulated residual envelopes.
• Updated the package title and description to cover distribution functions, Vasicek-type models, and the hyperbolic-secant kernel and HVASIQ family.
• Standardized boundary terminology as “augmented” and kernel terminology as “Vasicek-type” throughout the current documentation.
• Corrected the bodyfat documentation: it contains 10 variables, and its five response variables are proportions in (0, 1), not values on a 0–100 scale.
• Replaced generic quantile notation tau by p in the NVASIM quantile formula and corrected the description of the bivariate-normal CDF.
• Added a real-data ZOANVASIM example based on the boundary-valued inappropriate-stay proportion in aep.
• Extended the numerical derivative checks for all three quantile families to a grid of response, quantile, shape, and fixed-quantile values.
• Added the documented print.vasicek_envelope() S3 method and tests for the print and plot interfaces.
• Clarified that the reductions of ZOANVASIM at nu = 0 or tau = 0 are nested limiting cases in the closure of its open parameter space.
• Aligned the documented endpoint domains of the base d, p, and q functions with their implemented behavior.
• Corrected bibliographic page ranges, added the logistic-kernel reference to LVASIQ, expanded the package-level references, and documented all four included datasets in the package overview and README.
• Added direct distribution-identity and normalization tests for all three boundary-augmented models.

Hyperbolic-secant-kernel quantile regression

• Added the HVASIQ() GAMLSS family for conditional quantile regression with a hyperbolic-secant kernel and a user-specified fixed quantile level.
• Added compiled dHVASIQ(), pHVASIQ(), qHVASIQ(), and rHVASIQ() functions, including stable log-probability and tail calculations.
• Implemented closed-form first, second, and cross log-likelihood derivatives with respect to mu and sigma.
• Added randomized quantile residual support and numerical conditional-moment functions for the GAMLSS family.
• Extended vasicek_envelope() to fitted HVASIQ models.
• Corrected parametric-envelope simulation for quantile families so the fixed level stored in the fitted model is passed to their random generators.
• Added documentation and tests for distribution identities, normalization, fixed-quantile preservation, vectorization, analytical derivatives, conditional moments, random generation, and GAMLSS fitting.

Boundary-augmented mean regression

• Added the GAMLSS-conventional aliases d/p/q/rZANVASIM(), d/p/q/rOANVASIM(), and d/p/q/rZOANVASIM(). The established numbered names remain available. This correspondence allows likelihood-based methods such as vcov.gamlss() to locate each family’s density function.
• Added ZANVASIM(), a zero-augmented normal-kernel Vasicek mean family, with nu modeling the probability at zero.
• Added OANVASIM(), a one-augmented normal-kernel Vasicek mean family, with nu modeling the probability at one.
• Added ZOANVASIM(), a zero-and-one-augmented normal-kernel Vasicek mean family. In this family, nu is the probability at zero and tau is the conditional probability at one among nonzero observations.
• Added the corresponding d0NVASIM(), p0NVASIM(), q0NVASIM(), r0NVASIM(), d1NVASIM(), p1NVASIM(), q1NVASIM(), r1NVASIM(), d01NVASIM(), p01NVASIM(), q01NVASIM(), and r01NVASIM() functions.
• Added analytical derivatives, randomized quantile residuals, marginal moments, and GAMLSS fitting support for all three boundary-augmented families.

Simulated residual envelopes

• Added vasicek_envelope() for parametric-bootstrap simulated envelopes based on fitted gamlss objects.
• Added support for normalized randomized quantile residuals and generalized Cox–Snell residuals, with the latter defined from the same fitted probability integral transform and evaluated on the log-survival scale for numerical stability in the upper tail.
• Added pointwise percentile and pointwise minimum–maximum envelopes.
• Each accepted bootstrap sample is simulated from the fitted model, refitted, and used to recalculate and order the requested residuals.
• Added print and plot methods for vasicek_envelope objects. The documentation now distinguishes these full quantile–quantile plots from half-normal plots and explains the finite-sample simulated mean curve.
• Added a row-count check to automatic bootstrap refitting so data altered by missing-value removal or subset must be supplied explicitly or handled by a custom refit function.

Documentation and tests

• Standardized the R source filenames as dpqr-0NvasicekM.R, dpqr-1NvasicekM.R, and dpqr-01NvasicekM.R.
• Added numerical verification of all first, second, and cross derivatives for ZANVASIM, OANVASIM, and ZOANVASIM.
• Added tests of the randomized quantile residual expressions for the zero-augmented, one-augmented, and zero-and-one-augmented families, including the CDF jump intervals, interior observations, reproducibility, and simulation from the fitted family.
• Added tests for simulated residual envelopes, including argument validation, reproducibility, returned components, plotting, stable Cox–Snell upper-tail calculations, and incompatible refit data.
• Clarified the roles of x and q and distinguished the boundary behavior of the zero-augmented, one-augmented, and zero-and-one-augmented distributions.
• Updated the package overview to describe the boundary-augmented families and to distinguish the tau parameter in ZOANVASIM from the fixed quantile level used by NVASIQ and LVASIQ.
• Added a package-level example comparing OANVASIM and BEOI using the one-inflated accuracy1 response from the ReadingSkills data.
• Expanded the README references for the Vasicek distributions, GAMLSS, boundary-augmented models, randomized quantile and Cox–Snell residuals, simulated envelopes, and Rcpp.

vasicekreg 1.1.0 (2026-07-28)

Interface reorganization

• Renamed the normal-kernel mean family and distribution functions from VASIM to NVASIM.
• Renamed the normal-kernel quantile family and distribution functions from VASIQ to NVASIQ.
• Retained LVASIQ for the logistic-kernel quantile distribution functions.
• Renamed the corresponding R and C++ source files to identify the kernel (N or L) and parameterization (M or Q) explicitly.
• Renamed the internal Rcpp routines and regenerated their registration interfaces.
• Updated the namespace, documentation, examples, package overview, and tests for the new interface.

GAMLSS quantile level

• NVASIQ() does not accept tau as an argument. For GAMLSS fitting, tau must be defined as a scalar variable in the global environment.
• The distribution functions dNVASIQ(), pNVASIQ(), qNVASIQ(), and rNVASIQ() continue to accept tau explicitly.

Logistic-kernel quantile regression

• Added the LVASIQ() GAMLSS family for conditional quantile regression with the logistic-kernel Vasicek distribution.
• Implemented closed-form first, second, and cross derivatives with respect to mu and sigma; model fitting does not use numerical differentiation.
• Added quantile residual support and numerical moment functions for the family object.

vasicekreg 1.0.3 (2026-07-28)

Bug fixes

• Restored the missing implementation of qVASIM().
• Corrected log.p handling in all quantile functions.
• Corrected the bivariate-normal calculation used by the variance components of VASIM() and VASIQ().
• Made the fixed quantile level an explicit argument of VASIQ() and removed dependence on a global tau object.
• Corrected the second derivative with respect to mu in VASIQ().
• Added stable upper-tail calculations and consistent parameter-length checks to the C++ routines.

Documentation and tests

• Clarified that the logistic-kernel implementation currently provides distribution functions but not a GAMLSS family.
• Added executable tests for distribution identities, moments, derivatives, vectorization, and fixed-quantile handling.

vasicekreg 1.0.2 (2026-01-12)

Improvements

• Performance optimizations in dpqr-vasicekmean.R and dpqr-vasicekquant.R.

vasicekreg 1.0.1 (2021-12-05)

Bug fixes

• Corrected the term variance = function(mu, sigma) in the VASIM family.
• Corrected the term variance = function(mu, sigma) in the VASIQ family.

vasicekreg 1.0.0 (2021-07-05)

Initial release

• First release of the vasicekreg package on CRAN.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.