sptotal implements finite population block kriging (Ver Hoef (2008)), a geostatistical approach to predicting means and totals of count data for finite populations. sptotal is currently under development.


sptotal can be installed using devtools


Simple Example

The sptotal package can be used for spatial prediction in settings where there are a finite number of sites and some of these sites were not sampled. Note that, to keep this example simple, we are simulating response values that are spatially independent. In a real example, we assume that there is some spatial dependence in the response.

```{r, results = “hide”} set.seed(102910) spatial_coords <- expand.grid(1:10, 1:10) toy_df <- data.frame(xco = spatial_coords[ ,1], yco = spatial_coords[ ,2], counts = sample(c(rpois(50, 15), rep(NA, 50)), size = 100, replace = TRUE))

mod <- slmfit(formula = counts ~ 1, xcoordcol = “xco”, ycoordcol = “yco”, data = toy_df) summary(mod)

pred <- predict(mod) ## look at the predictions pred$Pred_df[1:6, c(“xco”, “yco”, “counts”, “counts_pred_count”)]

## Methods and Basic Functions

`sptotal` Main Functions:

`slmfit()` fits a spatial linear model to the response on the
observed/sampled sites. \code{check.variogram} can be used to construct
an empirical variogram of the residuals of the spatial linear model.

`predict.slmfit()` uses the spatial linear model fitted with `slmfit()` and finite
population block kriging to predict counts/densities at unobserved locations.
A prediction for the total count as well as a prediction variance
are given by default.

`get.predinfo()` and `get.predplot()` take the resulting object from
`predict.slmfit()` to construct (1) summary information, including the
prediction, prediction variance, and a prediction interval as well as
(2) a plot of the site-wise predictions.

For more details on how to use these functions, please see the Vignette by running


and clicking HTML.

The methods in this package are based on the following reference:

Ver Hoef, Jay M. “Spatial methods for plot-based sampling of wildlife populations.” 15, no. 1 (2008): 3-13.


To cite this package in the literature, run the following line: