r - ggplot2 help - superimposing GAMs to data + aesthetic changes -

so i'm trying create several plots on 1 time series plot using ggplot2.

here's reproducible code (i hope):

# read in data , libraries fishdata <- read.csv("http://dl.dropbox.com/s/nsttbnaj7bzpk1g/fishdata.hilsatotal.csv", header=t) attach(fishdata) require(mgcv) require(ggplot2)  # gams total.gam <- gam(totalfishfao ~ s(tonsaquaculturefao) +s(totalmarinefao),                   quasipoisson, fishdata) inland.gam <- gam(totalinlandfao ~ s(tonsaquaculturefao) + s(totalmarinefao),                    quasipoisson) hilsainland.gam <- gam(hilsashad.inland ~ s(tonsaquaculturefao) + s(totalmarinefao),                         quasipoisson) hilsatotal.gam <- gam(hilsasald.total ~ s(tonsaquaculturefao) + s(totalmarinefao),                        quasipoisson) gtfao.gam <- gam(grandtotal ~ s(totalmarinefao) + s(tonsaquaculturefao),                   quasipoisson)  # plot df3 <- data.frame(cbind(year, totalfishfao, totalinlandfao,                          hilsashad.inland, hilsasald.total, grandtotal)) df3 ddd <- melt(df3, id.vars="year") ddd ppp <- ggplot(ddd, aes(year, value, shape=variable, colour=variable)) +            geom_point() ppp_final <- ppp +                 xlab("year") +                ylab("catches (tons)") +                ggtitle("time series of target variables (1950-2011)")  ppp_final2 <- ppp_final +                  stat_smooth() +                 scale_colour_discrete(name = "target variable (fao)",                                       breaks = c("totalfishfao", "totalinlandfao", "hilsashad.inland", "hilsasald.total", "grandtotal"),                                      labels=c("total (marine + inland)", "inland", "hilsa shad inland", "hilsa shad total \n (marine + inland)", "grand total \n (marine + inland + aquaculture)")) +                 scale_shape_discrete(name = "target variable (fao)",                                      breaks = c("totalfishfao", "totalinlandfao", "hilsashad.inland", "hilsasald.total", "grandtotal"),                                       labels=c("total (marine + inland)", "inland", "hilsa shad inland", "hilsa shad total \n (marine + inland)", "grand total \n (marine + inland + aquaculture)")) +                 scale_x_continuous(breaks=seq(1950,2011,10)) ppp_final2 

i have 2 questions,

1) stat_smooth() uses loess method default, want use gam instead. want use gams above each corresponding target variable - there way of doing this? need superimpose model each target separately; if so, how?

2) there way change grand total (marine + inland + aquaculture) & hilsa shad total (marine + inland) filled shapes?

update 29-8-2013

i can want using plot:

plot(year, grandtotal, xlab="year", ylim=c(0,max(grandtotal)),ylab="catches (tons)",       main="time series of target variables \n gams & 95% ci intervals") #plot(gtfao.gam, select=1) mydata = data.frame(year, totalmarinefao, tonsaquaculturefao, grandtotal) pv <- predict(gtfao.gam, mydata, type="response", se=t) lines(mydata$year, pv$fit) lines(mydata$year, pv$fit + 2*pv$se.fit, lty=2) lines(mydata$year, pv$fit - 2*pv$se.fit, lty=2) #inland par(new=t) plot(year, totalinlandfao, ylim=c(min(0), max(grandtotal)), xlab="", ylab="") pvv <- predict(inland.gam, mydata, type="response", se=t) lines(mydata$year, pvv$fit) lines(mydata$year, pvv$fit + 2*pvv$se.fit, lty=2) lines(mydata$year, pvv$fit - 2*pvv$se.fit, lty=2) ### etc...... 

when use:

stat_smooth(method="gam", family="quasipoisson", method="gam",  family="quasipoisson", formula = totalfishfao ~ tonsaquaculturefao + totalmarinefao) 

i these errors:

error in data.frame(x = xseq, y = model$family$linkinv(as.vector(pred$fit)),  :    arguments imply differing number of rows: 80, 62 in addition: warning messages: 1: in predict.gam(model, newdata = data.frame(x = xseq), se = se, type = "link") :   not required variables have been supplied in  newdata!  2: 'newdata' had 80 rows variables found have 62 rows  error in if (nrow(layer_data) == 0) return() : argument of length 0 in addition: warning message: removed 68 rows containing missing values (geom_point).