Description Usage Arguments Details Value Author(s) See Also Examples

Obtains prediction of main effects plus spatial variability from a `georamps`

model fit.

1 2 |

`object` |
object returned by |

`newdata` |
data frame containing covariate values for the main effect, unmeasured spatial coordinates, and (if applicable) spatial variance indices with which to predict. |

`type` |
character string specifying the type of spatial prediction to perform. The default value |

`...` |
some methods for this generic require additional arguments. None are used in this method. |

Prediction will be performed only at the coordinates in `newdata`

that differ from those used in the initial `georamps`

model fitting. In particular, overlapping coordinates will be excluded automatically in the prediction.

`'predict.ramps'`

object, inheriting from class `'matrix'`

, of samples from the posterior predictive distribution. Labels for the samples at each new coordinate are supplied in the returned column names and MCMC iteration numbers in the row names. A matrix containing the new coordinates is supplied in the `coords`

attribute of the object.

Brian Smith [email protected]

`georamps`

`plot.predict.ramps`

,
`window.predict.ramps`

,

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ```
## Prediction for georamps example results
## Not run:
ct <- map("state", "connecticut", plot = FALSE)
lon <- seq(min(ct$x, na.rm = TRUE), max(ct$x, na.rm = TRUE), length = 20)
lat <- seq(min(ct$y, na.rm = TRUE), max(ct$y, na.rm = TRUE), length = 15)
grid <- expand.grid(lon, lat)
newsites <- data.frame(lon = grid[,1], lat = grid[,2],
measurement = 1)
NURE.pred <- predict(NURE.fit, newsites)
par(mfrow=c(2,1))
plot(NURE.pred, func = function(x) exp(mean(x)),
database = "state", regions = "connecticut",
resolution = c(200, 150), bw = 5,
main = "Posterior Mean",
legend.args = list(text = "ppm", side = 3, line = 1))
plot(NURE.pred, func = function(x) exp(sd(x)),
database = "state", regions = "connecticut",
resolution = c(200, 150), bw = 5,
main = "Posterior Standard Deviation",
legend.args = list(text = "ppm", side = 3, line = 1))
## End(Not run)
``` |

brian-j-smith/ramps documentation built on May 12, 2019, 5:44 a.m.

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