plot_sp3d {pspatreg}

Plot and mapping spatio-temporal trends.

Description

Make plots and maps of the spatio-temporal trends in 3d of the objects fitted with pspatfit function.

Usage

plot_sp3d(object, data, time_var, time_index, addmain = TRUE, addint = TRUE)

Arguments

object

object returned from pspatfit

data

sf object.

time_var

name of the temporal variable in data.

time_index

vector of time points to plot.

addmain

Add f1_main and f2_main plots in psanova case.

addint

Add f12_int in psanova case.

Value

plots and maps of the spatial trends

Author(s)

Roman Minguez	[e-mail]
Roberto Basile	[e-mail]
Maria Durban	[e-mail]
Gonzalo Espana-Heredia	[e-mail]

References

• Lee, D. and Durban, M. (2011). P-Spline ANOVA Type Interaction Models for Spatio-Temporal Smoothing. Statistical Modelling, (11), 49-69. <doi:10.1177/1471082X1001100104>

• Eilers, P. and Marx, B. (2021). Practical Smoothing. The Joys of P-Splines. Cambridge University Press.

• Fahrmeir, L.; Kneib, T.; Lang, S.; and Marx, B. (2021). Regression. Models, Methods and Applications (2nd Ed.). Springer.

• Wood, S.N. (2017). Generalized Additive Models. An Introduction with R (second edition). CRC Press, Boca Raton.

Examples

library(pspatreg)
library(sf)
data(unemp_it, package = "pspatreg")
lwsp_it <- spdep::mat2listw(Wsp_it)
unemp_it_sf <- st_as_sf(dplyr::left_join(
                               unemp_it, map_it,  
                        by = c("prov" = "COD_PRO")))
######## FORMULA of the model
form3d_psanova_restr <- unrate ~ partrate + agri + cons +
                        pspl(serv, nknots = 15) + 
                        pspl(empgrowth, nknots = 20) +
                        pspt(long, lat, year, 
                             nknots = c(18, 18, 8),
                             psanova = TRUE, 
                             nest_sp1 = c(1, 2, 3), 
                             nest_sp2 = c(1, 2, 3),
                             nest_time = c(1, 2, 2),
                             f1t = FALSE, f2t = FALSE)


####### FIT the model
sp3danova <- pspatfit(form3d_psanova_restr, 
                      data = unemp_it_sf)
summary(sp3danova)                          

###### Plot spatio-temporal trends for different years
plot_sp3d(sp3danova, data = unemp_it_sf, 
          time_var = "year", 
          time_index = c(1996, 2005, 2019),
          addmain = FALSE, addint = FALSE)
###### Plot of spatio-temporal trend, main effects 
######      and interaction effect for a year
plot_sp3d(sp3danova, data = unemp_it_sf, 
          time_var = "year", 
          time_index = c(2019),
          addmain = TRUE, addint = TRUE)
          
#### Plot of temporal trend for each province
plot_sptime(sp3danova, 
            data = unemp_it, 
            time_var = "year", 
            reg_var = "prov")