[R] Help with Using spTimer or spTDyn to estimate "GP" Model
Bert Gunter
bgunter@4567 @end|ng |rom gm@||@com
Sun Jan 31 21:34:45 CET 2021
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On Sun, Jan 31, 2021 at 11:26 AM alex_rugu--- via R-help <
r-help using r-project.org> wrote:
> When I run the following scripts I get the following error and I do not
> understand the source. I believe N is specified as the number of
> observations by year in the time series variables. The error is
> #######################################
> Output: GP models
> Error in spGP.Gibbs(formula = formula, data = data, time.data =
> time.data, :
> Error: Years, Months, and Days are misspecified,
> i.e., total number of observations in the data set should be equal to N
> : N = n * r * T
> where, N = total number of observations in the data,
> n = total number of sites,
> r = total number of years,
> T = total number of days.
> ## Check spT.time function.
>
> The scrip is
> ######################
> library(spTimer)
> library(spTDyn)
> library(tidyverse)
> library(ggmap)
>
>
> register_google(key=" your key ") # for use with ggmap
> getOption("ggmap")
>
>
> #Data to analyze is from plm package
> #The data include US States Production, which is a panel of 48
> observations from 1970 to 1986
> #A data frame containing :
> #state: the state
> #year : the year
> #region : the region
> #pcap : public capital stock
> #hwy : highway and streets
> #water : water and sewer facilities
> #util : other public buildings and structures
> #pc : private capital stock
> #gsp : gross state product
> #emp :labor input measured by the employment in non–agricultural payrolls
> #unemp : state unemployment rateA panel of 48 observations from 1970 to
> 1986
>
>
> data("Produc", package = "plm")
> glimpse(Produc)
>
>
> #Estimate Geolocation of states to account for spill over effects
> states_df <- data.frame(as.character(unique(Produc$state)))
> names(states_df)<- c("state")
>
>
> state_geo_df <- mutate_geocode(states_df, state)
>
> #Join the data
>
> Product_geo <- full_join(state_geo_df, Produc)
> glimpse(Product_geo)
>
>
> #Create the time series variable
> #number of state
> ns <- length(unique(Product_geo$state))
>
>
> #number of year
> ny <- length(unique(Product_geo$year))
> ####################################################
> # I want to do Spatio-Temporal Bayesian Modeling Using spTimer or spTDyn
> #defines the time series in the Spatio-temporal data.
>
>
> ts_STD <- def.time(t.series=ns, segments=ny)
>
>
> ##################Estimate the model using spTDyn package
> #Also note that the spT.Gibbs in spTimer gives the same error
>
>
> GibbsDyn(gsp ~ pcap + hwy + water + util + pc ,
> data=Product_geo, model="GP",
> time.data=ts_STD,
> coords=~lon + lat,
> nItr=5000, nBurn=1000, report=1, tol.dist=0.05,
> distance.method="geodetic:km", cov.fnc="exponential",
>
> spatial.decay=decay(distribution="FIXED"),truncation.para=list(at=0,lambda=2))
>
>
> #Also I will appreciate showing how to deal with unbalanced panel data
> #Delete some of the rows
> Product_geo$cond = with(Product_geo, if_else(state=="ALABAMA" &
> year==1971, 0,
> if_else(state=="COLORADO" &
> year==1971 | year==1973 , 0,
> if_else(state=="TEXAS" &
> year==1971 | year==1973 | year==1985, 0, 1))))
>
> #Create an unbalanced panel
> Product_geo_unb <- Product_geo %>% filter(cond==1) %>% select(-cond)
> glimpse(Product_geo_unb)
>
>
> #How to use GibbsDyn or spT.Gibbs function to estimate the "GP" model for
> such unbalanced panel data?
>
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