New invest() methods for "survfit" and "Surv" objects (from the survival package) estimate the survival time at which a Kaplan-Meier curve reaches a given survival probability (e.g., median survival time), with confidence limits obtained by inverting the curve's pointwise confidence band (#30).
invest() results with interval = "percentile" now also inherit from class "boot", so they work directly with functions from the boot package such as boot::boot.ci() (#32).
nlme moved from Imports to Suggests; "lme"-specific code paths now check for it with requireNamespace() (#47).
Fixed calibrate.lm() silently mishandling models with poly()-transformed predictors; it now reads the predictor from the model frame and errors informatively instead (#48).
Fixed the formula for g in the inversion-interval vignette, which had been broken by a regression in a prior "typo fix" (#51).
Fixed predFit() with se.fit = TRUE failing on "nls" models with more than one predictor variable (#53).
Fixed invest() and predFit() failing when the fitted model was created inside a function, or with no data argument at all; training/prediction data is now reconstructed via model.frame() or the environment captured by the model's formula, instead of evaluating object$call$data in the caller's frame (#41, #42, #45).
invest() now validates that newdata columns have classes (and, for factors, levels) compatible with the fitted model's training data, rather than failing with a confusing downstream error or silently returning a nonsensical result (#36).
The "Use plotFit for guidance" hint on a failed confidence-limit search no longer appears for multi-predictor lm/glm models, since plotFit() doesn't support more than one predictor variable (#35).
Fixed the output of predFit() in situations whenever standard errors and confidence/predictions bands are both requested.
New data sets bladder (a repeated measures data set) and whisky.
Fixed typos in documentation throughout the package.
Updated URLs throughout the package.
Better y-axis limits when x-axis is on log scale (e.g., using log = "x"). Fixes issue #27.
Better default y-axis label when using plotFit() on a model with transformed response. For example, calling plotFit(fit) where fit <- lm(sqrt(dist) ~ speed, data = cars) will have a default y-axis label of "sqrt(dist)".
plotFit() has been completely re-written using much less code.
predFit() (and hence plotFit()) now works for "nls" objects fit using the Golub-Pereyra algorithm (i.e., algorithm = "plinear"); however, confidence/prediction bands are still not available.
New introductory vignette.
Multiple predictor variables are allowed for "lm" and "glm" objects.
All non-base package functions are now imported.
The generic function predFit() is now exported. This function is used by investr
to obtain predictions, and hence, inverse predictions. For example, predFit()
can be used to obtain prediction intervals for nonlinear least-squares fits
(i.e., models of class "nls").
Improved tests and test coverage.
plotFit() gained methods for "rlm" and "lqs" objects from package MASS.
invest() now accepts objects of class "glm" (experimental).
Functions calibrate() and invest() now return an object of class "invest".
Cleaned up documentation.
Added AnyNA() function for those using older versions of R.
Cleaned up examples.
Added bootstrap option to invest().
Updated citation file.
Minor code changes.
plotFit() should now plot models with transformed responses correctly.
Fixed error causing invest() to fail because of a missing data argument.
Added more tests.
invest() now accepts objects of class "lme" (experimental).
A few minor bug fixes and code improvements.
Added more tests.
A few minor bug fixes.
Slightly better documentation.