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lande 0.1.0

First release.

• Selection differentials and linear, quadratic and correlational gradients on relative fitness, with p-values from the logistic model for survival and from a Poisson or negative binomial model for counts.
• Cubic spline fitness functions with a bootstrap band, two-trait fitness surfaces drawn only where there are data, and adaptive landscapes of mean fitness for one or two traits.
• count_family = "quasipoisson" or "nb" in univariate_spline(), correlated_fitness_surface() and temporal_landscape() for overdispersed counts; the spline and the surface report the dispersion.
• by_group = TRUE in the spline and the surface fits each group on its own and returns a list of fits.
• Several groups on one surface, with each group’s mean and highest point marked, and interior peaks told from maxima at the edge of the data.
• Fitness functions and landscapes fitted period by period.
• Bootstrap standard errors and percentile intervals for the gradients, and leave-one-out (HC3) standard errors with se_type = "hc3".
• Assumption checks in one table: multivariate normality of the traits, VIF, rows per term, residuals or dispersion of the gradient model.
• Bumpus’s sparrows, Martin’s pupfish and two sets of Galapagos finches bundled as datasets, with CSV copies of the pupfish and finch data in extdata.
• A Shiny app that runs the analyses in a browser, opened with run_app(), which writes out the R calls that repeat an analysis with the current settings.
• canonical_analysis() rotates the gamma matrix to its canonical axes, with double-regression standard errors, permutation p-values (Reynolds et al. 2010) and an optional bootstrap, and plot_canonical_axes() draws fitness along them.
• Standard errors and a band on the GAM fitness surface, drawn with the plots’ uncertainty option, and peak_difference() to compare two points of a surface, or each with the pass between them (route = "line" for the straight line).
• The adaptive landscape reports how much of each simulated population falls outside the data, and flags an optimum on the edge of the grid; the plot can mark where the population leaves the data.
• A clamp option on the landscape and the thin-plate surface holds predicted fitness inside the range of the fitness type; on by default.

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.
Health stats visible at Monitor.