spind
v2.2.1Removed unneeded functions from Namespace
Makes WRM a lot noisier when the model breaks.
spind
v2.2.0deprecated customize_plot
and plot
arguments in favor of new plot
methods
for GEE
and WRM
.
GEE
and WRM
now return the ggplot
object in their respective classes.
Users can modify them from there rather than use the clunky interface to
modify them within the model function call.rvi.plot
and th.indep
now return
ggplot
as list items along with the values that they returned before.
customize_plot
arguments have been deprecated in every function it appears in.
plot.ROC
in th.indep
is also deprecated.
covar.plot
's customize_plot
argument is also deprecated, but the plot
argument is not, as this controls which statistic is plotted (variance or covariance)
rather than whether or not a plot is generated at all. This function no longer
prints the ggplot
object by default, but returns it as part of a list.
deprecated color.maps
arguments to upscale
and adjusted.actuals
.
Some documentation clarification and typo fixes.
Updated a couple error messages for consistency across functions.
Behind the scenes, moved all plotting functions that use ggplot2
to tidy
evaluation equivalents. If you're interested, more on that here.
spind
v2.1.3-Updated citation information.
spind
v2.1.2-Updated plot outputs from GEE
and WRM
so that y-axes aren't absurdly packed when autocorrelation values are very large
-Updated documentation for some modeling functions to reflect that factors as expanatory variables are not supported by spind
-Added some continuous integration functionality to the development branch to ensure that bugs are caught faster. No package functionality is affected by this
spind
v2.1.1-fix bug in predict.WRM
that prevented calculating smooth components
-fix bug in scaleWMRR
that prevented acfft from being called internally
-added trace
argument to mmiGEE
-updated vignette to teach users how to customize plots
spind
v2.1.0-Updated step.spind
model hierarchy recognition algorithm for improved efficiency and generality. Additionally reformatted code so no error message is produced when the initial model is the best model.
-Fixed examples in wavevar
and wavecovar
which called a non-existant function.
-Updated the package vignette for clarity and formatting. Additionally, removed pointless WRM example (padding with mean values) because the particular case being demonstrated was identical to first example.
-Added prettier plots from GEE
, WRM
, covar.plot
, rvi.plot
, and th.indep
using ggplot2
graphics. These functions should produce publication quality graphics, rather than the bare bones, minimalist approach in the previous versions of the package.
-Provide optional color palettes for graphical outputs of adjusted.actuals
and upscale
so they are more aesthetically pleasing.
-Updated argument names for a couple functions to ensure consistency throughout the package.
spind
v2.0.1-Updated vignette to newest version. Old version is not well developed. -added citation() to package
spind
v2.0.0introduces functions for implementing GEEs and WRMs in the context of spatial models in R. We are also including multiple model selection options for you to find the best model possible for your data. We have retained all of the original functions to calculate spatially corrected measures of model fit.
We've added wrappers for the gee
and geese
functions found in packages gee
and geepack
so that they can be implemented for spatial models. We've also added S3 methods for summary
and predict
to make them easy to interact with.
In addition to wrappers for GEEs, we've added wrappers for functions found in the waveslim
package that allow you to implement wavelet-revised models on spatial data sets. As with GEEs, we've also added S3 methods for predict
and summary
.
We've added functions to conduct multi-model inference and stepwise model selection (backwards only for the time being), as well as a slew of helper and utility functions to examine your model in greater detail.
The spatial indices included in the original release should still work as they did before.
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