Prediction of Dengue Outbreaks Based on Disease Surveillance and Meteorological Data
Home Page: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152688
This repository houses the code and data used in the analysis for the manuscript "Prediction of Dengue Outbreaks based on Disease Surveillance and Meteorological Data", by Aditya L. Ramadona et al.
I am running through your code trying to understand how the graphs were made. I keep coming across the following problem,
When I run this code:
`library(mgcv)
attach(training)
form <- as.formula("dengue ~ s(templ3,k=4)+s(rainl2,k=4)+s(rainl3,k=4)+s(denguel2,k=4)+s(denguel24,k=4)")
mod.train <- gam(form, family=quasipoisson, na.action=na.exclude, data=training)
detach(training)`
I receive the following results:
attach(training)
The following objects are masked by .GlobalEnv:
census, dengue, denguel0, denguel1, denguel2, denguel24, denguel3, denguel4, hum, huml0, huml1, huml2, huml3, huml4, month, rain, rainl0,
rainl1, rainl2, rainl3, rainl4, temp, templ0, templ1, templ2, templ3, templ4, X, year
The following objects are masked from training (pos = 3):
census, dengue, dengue_ma0211, dengue_ma0212, dengue_ma0213, dengue_ma0223, dengue_ma0224, dengue_ma0225, dengue_ma0235, dengue_ma0236,
dengue_ma0237, dengue_ma0247, dengue_ma0248, dengue_ma0249, dengue_ma0259, dengue_ma0260, dengue_ma1136, dengue_ma1148, dengue_ma1248,
dengue_ma1323, dengue_ma1348, dengue_ma2324, dengue_ma2335, dengue_ma2337, dengue_ma2348, dengue_ma2425, dengue_ma2435, dengue_ma2437,
dengue_ma2448, dengue_ma2535, dengue_ma2548, dengue_ma3747, dengue_ma4959, denguel0, denguel1, denguel10, denguel11, denguel12, denguel13,
denguel14, denguel15, denguel16, denguel17, denguel18, denguel19, denguel2, denguel20, denguel21, denguel22, denguel23, denguel24, denguel25,
denguel26, denguel27, denguel28, denguel29, denguel3, denguel30, denguel31, denguel32, denguel33, denguel34, denguel35, denguel36, denguel37,
denguel38, denguel39, denguel4, denguel40, denguel41, denguel42, denguel43, denguel44, denguel45, denguel46, denguel47, denguel48, denguel49,
denguel5, denguel50, denguel51, denguel52, denguel53, denguel54, denguel55, denguel56, denguel57, denguel58, denguel59, denguel6, denguel60,
denguel7, denguel8, denguel9, figures, hum, huml0, huml1, huml2, huml3, huml4, irA, irAl0, irAl1, irAl10, irAl11, irAl12, irAl13, irAl14,
irAl15, irAl16, irAl17, irAl18, irAl19, irAl2, irAl20, irAl21, irAl22, irAl23, irAl24, irAl25, irAl26, irAl27, irAl28, irAl29, irAl3, irAl30,
irAl31, irAl32, irAl33, irAl34, irAl35, irAl36, irAl37, irAl38, irAl39, irAl4, irAl40, irAl41, irAl42, irAl43, irAl44, irAl45, irAl46, irAl47,
irAl48, irAl49, irAl5, irAl50, irAl51, irAl52, irAl53, irAl54, irAl55, irAl56, irAl57, irAl58, irAl59, irAl6, irAl60, irAl7, irAl8, irAl9, irB,
irBl0, irBl1, irBl10, irBl11, irBl12, irBl13, irBl14, irBl15, irBl16, irBl17, irBl18, irBl19, irBl2, irBl20, irBl21, irBl22, irBl23, irBl24,
irBl25, irBl26, irBl27, irBl28, irBl29, irBl3, irBl30, irBl31, irBl32, irBl33, irBl34, irBl35, irBl36, irBl37, irBl38, irBl39, irBl4, irBl40,
irBl41, irBl42, irBl43, irBl44, irBl45, irBl46, irBl47, irBl48, irBl49, irBl5, irBl50, irBl51, irBl52, irBl53, irBl54, irBl55, irBl56, irBl57,
irBl58, irBl59, irBl6, irBl60, irBl7, irBl8, irBl9, month, rain, rainl0, rainl1, rainl2, rainl3, rainl4, temp, templ0, templ1, templ2, templ3,
templ4, time, X, year
form <- as.formula("dengue ~ s(templ3,k=4)+s(rainl2,k=4)+s(rainl3,k=4)+s(denguel2,k=4)+s(denguel24,k=4)")
mod.train <- gam(form, family=quasipoisson, na.action=na.exclude, data=training)
Error in smooth.construct.tp.smooth.spec(object, dk$data, dk$knots) :
NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning messages:
1: In mean.default(xx) : argument is not numeric or logical: returning NA
2: In Ops.factor(xx, shift[i]) : ‘-’ not meaningful for factors
detach(training)
How can I avoid this error? Did you manipulate the data you provided to omit NA's before running it?
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