View source: R/convenience-functions.R
| sp_diag | R Documentation | 
Visual diagnostics for areal data and model residuals
sp_diag(y, shape, ...)
## S3 method for class 'geostan_fit'
sp_diag(
  y,
  shape,
  name = "Residual",
  plot = TRUE,
  mc_style = c("scatter", "hist"),
  style = c("W", "B"),
  w = y$C,
  rates = TRUE,
  binwidth = function(x) 0.5 * stats::sd(x, na.rm = TRUE),
  size = 0.1,
  ...
)
## S3 method for class 'numeric'
sp_diag(
  y,
  shape,
  name = "y",
  plot = TRUE,
  mc_style = c("scatter", "hist"),
  style = c("W", "B"),
  w = shape2mat(shape, match.arg(style)),
  binwidth = function(x) 0.5 * stats::sd(x, na.rm = TRUE),
  ...
)
| y | A numeric vector, or a fitted  | 
| shape | An object of class  | 
| ... | Additional arguments passed to  | 
| name | The name to use on the plot labels; default to "y" or, if  | 
| plot | If  | 
| mc_style | Character string indicating how to plot the residual Moran coefficient (only used if  | 
| style | Style of connectivity matrix; if  | 
| w | An optional spatial connectivity matrix; if not provided and  | 
| rates | For Poisson and binomial models, convert the outcome variable to a rate before plotting fitted values and residuals. Defaults to  | 
| binwidth | A function with a single argument that will be passed to the  | 
| size | Point size and linewidth for point-interval plot of observed vs. fitted values (passed to  | 
When provided with a numeric vector, this function plots a histogram, Moran scatter plot, and map.
When provided with a fitted geostan model, the function returns a point-interval plot of observed values against fitted values (mean and 95 percent credible interval), a Moran scatter plot for the model residuals, and a map of the mean posterior residuals (means of the marginal distributions). If if mc_style = 'hist', the Moran scatter plot is replaced by a histogram of Moran coefficient values calculated from the joint posterior distribution of the residuals.
A grid of spatial diagnostic plots. If plot = TRUE, the ggplots are drawn using grid.arrange; otherwise, they are returned in a list. For the geostan_fit method, the underlying data for the Moran coefficient (as required for mc_style = "hist") will also be returned if plot = FALSE.
me_diag, mc, moran_plot, aple
data(georgia)
sp_diag(georgia$college, georgia)
bin_fn <- function(y) mad(y, na.rm = TRUE)
sp_diag(georgia$college, georgia, binwidth = bin_fn)
fit <- stan_glm(log(rate.male) ~ log(income),
                data = georgia,
                centerx = TRUE,
                chains = 1, iter = 1e3) # for speed only
sp_diag(fit, georgia)
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