dsims 0.2.0
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New Features

 * Delta selection criteria is now recorded as the difference in informtion criteria between the top 2 best fitting models as determined by the information criteria.]
 * The iteration numbers generating warnings or errors are now stored and displayed so user can choose what to do with these results.

Bug Fixes

 * Fixed missing RMSE values
 * Fix strata re-ordering for cluster size
 * Models with -Inf information criteria no longer selected
 * Models with dht = NULL are no longer selected
 * Models which predict detection values < 1 no longer cause errors and are correctly excluded.
 * Detectibility parameters for continuous covariates are now checked and validated.
 * Fix situation where all reps are to be excluded due to problematic model fitting.

dsims 0.1.0
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Introducing the new Distance Sampling Simulation package!

dsims is our latest simulation package which interfaces with dssd so designs can be generated within R, thus making the simulation process a lot easier! Dsims also makes use of ggplot to produce cleaner looking graphics.

Region and Design

 * dsims can make use of the region creation and all the designs currently in dssd.

Density

 * dsims can generate density objects from constant values for each strata, from fitted mgcv gam objects with x and y as explantory covariates and from formulas of x and y.
 * Density grids are stored as sf polygons with their associated x, y central coordinates and density value

Population Description

 * Populations can either be created with fixed population sizes or based on the densities in the density grid.
 * Both discrete and continuous individual level covariates can be included in the population

Detectablity

 * The detectability of the population can be described by either half normal, hazard rate or uniform detection shapes. Parameters can vary by stratum
 * Covariate parameters can be included to modify the scale parameter for each individual based on their covariate values.

 Analyses

 * A number of detection function analyses can be incorporated in a simulation and the model with the lowest criterion (AIC / AICc / BIC) will be selected.
 * Defining analyses is based on the arguments which are passed to our Distance R library.

 Simulations

 * Simulations can be run in serial or parallel and their progress is output.
 * The function run.survey can be used to create a single instance of a survey and check the simulation setup.

