Added minimum version numbers for rvec and poputils.
bage 0.7.5.1
Bug fixes
Fixed bug in code for simulating from Lin() and Lin_AR() priors.
bage 0.7.5
Changes to interface
Added arguments method and vars_inner to fit(). When method is "standard" (the default) fit() uses the existing calculation methods. When method is "inner-outer", fit() uses a new, somewhat experimental calculation method that involves fitting an inner model using a subset of variables, and then an outer model using the remaining variables. With big datasets, "inner-outer" can be faster, and use less memory, but give very similar results.
Added information on numbers of parameters, and standard deviations to output for print. Thank you to Duncan Elliot for suggesting printing numbers of parameters.
Changes to calculations
fit() now internally aggregates input data before fitting, so that cells with the same combinations of predictor variables are combined. This increases speed and reduces memory usage.
Changes to documentation
Added help for print.bage_mod
bage 0.7.4
CRAN release: 2024-08-28
Changes to interface
Function ssvd() no longer exported. Will export once package bssvd matures.
Added first data model. New function is set_datamod_outcome_rr3(), which deals with the case where the outcome variable has been randomly rounded to base 3.
augment() now creates a new version of the outcome variable if (i) the outcome variable has NAs, or (ii) a data model is being applied to the outcome variable. The name of the new variable is created by added a . to the start of the name of the outcome variable.
A help page summarising available data models
bage 0.7.1
Changes to interface
There are now three choices for the standardization argument: "terms", "anova", and "none". With "terms", all effects, plus assoicated SVD coefficients, and trend, cyclical, and seasonal terms, are centered independently. With "anova", the type of standardization descibed in Section 15.6 of Gelman et al (2014) Bayesian Data Analysis, is applied to the effects.
bage 0.7.0
Changes to calculations
Further simplification of standardization, but likely in future to split into two types of standardization: one that gives an ANOVA-style decomposition of effects, and one that helps with understanding the dynamics of each term.
Changes to infrastructure
Added Makevars file.
Changes to documentation
Stopped referring to second-order walks as equivalent to random walks with drift. (A second-order random walk differs from a random walk in that the implied drift term in a second-order random walk can vary over time.)
bage 0.6.3
Changes to calculations
Changed standardization of forecasts so that forecasts are standardized along the ‘along’ dimension by choosing the values that makes them consistent with time trends in the estimation period, and then standardizing within each value of the along dimensions.
bage 0.6.2
Changes to interface
Removed SVDS(), SVDS_AR(), SVDS_AR1(), SVDS_RW(), and SVDS_RW2() priors. Added indep argument to corresponding SVD priors. SVD priors now choose between ‘total’, ‘independent’ and ‘joint’ models based on (1) the value of indep argument, (2) the value of var_sexgender and the name of the term.
Changes to data
Object HMD now contains 5 components, rather than 10.
bage 0.6.1
Changes to calculations
Fixed problems with standardization of forecast
Added an intercept term to Lin() and LinAR() priors
bage 0.6.0
Issues
Standardization of forecasts not working correctly.
Changed values that are stored in object: removed draws_linpred, added draws_effectfree, draws_spline, and draws_svd. Modified/added downstream functions.
Calculation of ‘along_by’ and ‘agesex’ matrices pushed downwards into lower-level functions.
bage 0.5.1
Changes to interface
Moved HMD code to package bssvd.
bage 0.5.0
Changes to interface
Combined interaction (eg ELin) and main effect (eg Lin) versions of priors
augment() method for bage_mod objects now calculated value for .fitted in cases where the outcome or exposure/size is NA, rather than setting the value of .fitted to NA.
Internal calculations
Standardization of effects only done if components() is called. augment() uses the linear predictor (which does not need standardization.)
Internally, draws for the linear predictor, the hyper-parameters and (if included in model) disp are stored, rather than the full standardized components.
Standardization algorithm repeats up to 100 times, or until all residuals are less than 0.0001.
With the new configuration, calculations for large matrices that previously failed with error message “Internal error: Final residual not 0” are now running.
Simulations
When drawing from the prior, the intercept is always set to 0. Terms with SVD or Known priors are not touched. All other terms are centered.
bage 0.4.0
Changes to back-end for SVD priors
Move most functions for creating ‘bage_ssvd’ objects to package ‘bssvd’.
Allowed number of components of a ‘bage_ssvd’ object to differ from
Bug fixes
Corrected error in calculation of logit in ssvd_comp().