NEWS for package moult
moult 2.3.0
- Added bootstrap confidence intervals (confint.moult function), estimates of covariance matrix and standard errors.
- Added dfbeta.moult function to check influence of individual observations.
- Updated predict.moult function.
- Components for likelihood function are calculated once and components to return are selected depending on type.
- Fixed format error in help files.
moult 2.2.1
- Fixed error in as.vector(data.frame).
moult 2.2.0
- Fixed error in the calculation of SE(SD in start of moult). Thanks to Les Underhill and Tanya Scott for picking this up.
- Moult scores in half steps can be converted to proportion of feather mass grown, e.g. "5 5 5 5 4.5 2 0 0 0" (ms2pfmg).
Changes in version 2.1.0
- moult_alternative provides alternative parameterization, with halfway date instead of start of moult. Still in testing phase. At later stage will be incorporated into moult function.
- Addition of prec parameter to define measurement precision of moult index (proportion of feather mass grown).
- Bug fix in type 3 likelihood, now more likely to complete optimization.
- New vignette for individual primary analysis.
Changes in version 2.0.0
- Likelihood is calculated differently: not estimated by density but by integrating between y - 0.02 and y + 0.02, where y is the moult score, or PFMG.
- 'moult' function now allows fixed parameters.
Changes in version 1.4
-- Fixed error in predict.moult.
Changes in version 1.3
-- Bug fix: moult function did not work when added covariates for standard deviation in start date.
Now works, but still only for categorical covariates.
-- Improved row and column names for covariance matrix of parameter estimates.
Changes in version 1.2
-- Added reference to article in Journal of Statistical Software.
Changes in version 1.1
-- The 'weaver' data set now contains only adult birds, and only observations
from years 1988-2005.
-- 'formula' in function 'moult' has changed to 'moult.index ~ days | x1 + x2 | y1 + y2 | z1',
where the x's are covariates for duration, the y's are covariates for mean start date of
moult and the z can be a single categorical covariate for the standard deviation in start
of moult.
-- The above change depends on package 'Formula'.
-- 'moult' now has a 'data' argument, similar to 'lm' or 'glm'.
-- 'predict.moult' can now be used for predicting mean start dates at different covariate settings.