hatchPlot | R Documentation |
This function visualizes the map with different variables. The input data frame can be either the long or wide format.
hatchPlot( data, variables, values = NULL, labels = NULL, geo, by.data, by.geo, is.long = FALSE, lower, upper, lim = NULL, lim.CI = NULL, breaks.CI = NULL, ncol = 4, hatch = NULL, border = NULL, size = 1, legend.label = NULL, per1000 = FALSE, direction = 1, ... )
data |
a data frame with variables to be plotted |
variables |
vector of variables to be plotted. If long format of data is used, only one variable can be selected |
values |
the column corresponding to the values to be plotted, only used when long format of data is used |
labels |
vector of labels to use for each variable, only used when wide format of data is used |
geo |
SpatialPolygonsDataFrame object for the map |
by.data |
column name specifying region names in the data |
by.geo |
variable name specifying region names in the data |
is.long |
logical indicator of whether the data is in the long format, default to FALSE |
lower |
column name of the lower bound of the CI |
upper |
column name of the upper bound of the CI |
lim |
fixed range of values for the variables to plot |
lim.CI |
fixed range of the CI widths to plot |
breaks.CI |
a vector of numerical values that decides the breaks in the CI widths to be shown |
ncol |
number of columns for the output tabs |
hatch |
color of the hatching lines. |
border |
color of the polygon borders. |
size |
line width of the polygon borders. |
legend.label |
Label for the color legend. |
per1000 |
logical indicator to plot mortality rates as rates per 1,000 live births. Note that the added comparison data should always be in the probability scale. |
direction |
Direction of the color scheme. It can be either 1 (smaller values are darker) or -1 (higher values are darker). Default is set to 1. |
... |
unused. |
Zehang Richard Li, Katie Wilson
## Not run: years <- levels(DemoData[[1]]$time) # obtain direct estimates data <- getDirectList(births = DemoData, years = years, regionVar = "region", timeVar = "time", clusterVar = "~clustid+id", ageVar = "age", weightsVar = "weights", geo.recode = NULL) # obtain direct estimates data_multi <- getDirectList(births = DemoData, years = years, regionVar = "region", timeVar = "time", clusterVar = "~clustid+id", ageVar = "age", weightsVar = "weights", geo.recode = NULL) data <- aggregateSurvey(data_multi) fit2 <- smoothDirect(data = data, geo = geo, Amat = mat, year_label = years.all, year_range = c(1985, 2019), rw = 2, is.yearly=TRUE, m = 5, type.st = 4) out2 <- getSmoothed(fit2) plot(out2, is.yearly=TRUE, is.subnational=TRUE) hatchPlot(data = subset(out2, is.yearly==FALSE), geo = geo, variables=c("years"), values = c("median"), by.data = "region", by.geo = "REGNAME", lower = "lower", upper = "upper", is.long=TRUE) ## End(Not run)
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