## ----message = FALSE----------------------------------------------------------
library(climwin)

## ----eval = FALSE-------------------------------------------------------------
# 
# MassWin <- slidingwin(xvar = list(Temp = MassClimate$Temp),
#                       cdate = MassClimate$Date,
#                       bdate = Mass$Date,
#                       baseline = lm(Mass ~ 1, data = Mass),
#                       cinterval = "day",
#                       range = c(150, 0),
#                       type = "absolute", refday = c(20, 05),
#                       stat = "mean",
#                       func = "lin")
# 

## ----eval = FALSE-------------------------------------------------------------
# 
#     head(MassWin[[1]]$Dataset)
# 

## ----eval = FALSE-------------------------------------------------------------
# 
#     MassWin[[1]]$BestModel
# 

## ----eval = FALSE-------------------------------------------------------------
# 
# Call:
# lm(formula = Yvar ~ climate, data = modeldat)
# 
# Coefficients:
# (Intercept)      climate
#     163.544       -4.481
# 

## ----eval = FALSE-------------------------------------------------------------
# 
#     head(MassWin[[1]]$BestModelData)
# 

## ----eval = FALSE-------------------------------------------------------------
# 
# MassRand <- randwin(repeats = 5,
#                     xvar = list(Temp = MassClimate$Temp),
#                     cdate = MassClimate$Date,
#                     bdate = Mass$Date,
#                     baseline = lm(Mass ~ 1, data = Mass),
#                     cinterval = "day",
#                     range = c(150, 0),
#                     type = "absolute", refday = c(20, 05),
#                     stat = "mean",
#                     func = "lin")
# 

## ----eval = F-----------------------------------------------------------------
# 
# MassRand[[1]]
# 

## ----eval = F-----------------------------------------------------------------
# 
# pvalue(dataset = MassWin[[1]]$Dataset, datasetrand = MassRand[[1]], metric = "C", sample.size = 47)
# 

## ----eval = F-----------------------------------------------------------------
# 
# 1.94e-05
# 

## ----fig.width = 4, fig.height = 4, message = FALSE---------------------------

plothist(dataset = MassOutput, datasetrand = MassRand)


## ----fig.width = 4, fig.height = 4--------------------------------------------

plotdelta(dataset = MassOutput)


## ----fig.width = 4, fig.height = 4--------------------------------------------

plotweights(dataset = MassOutput)


## ----fig.width = 4, fig.height = 4--------------------------------------------

plotbetas(dataset = MassOutput)


## ----fig.width = 4, fig.height = 4--------------------------------------------

plotwin(dataset = MassOutput)


## -----------------------------------------------------------------------------

MassSingle <- singlewin(xvar = list(Temp = MassClimate$Temp),
                        cdate = MassClimate$Date,
                        bdate = Mass$Date,
                        baseline = lm(Mass ~ 1, data = Mass),
                        cinterval = "day",
                        range = c(72, 15),
                        type = "absolute", refday = c(20, 5),
                        stat = "mean",
                        func = "lin")


## ----fig.width = 6, fig.height = 6--------------------------------------------

plotbest(dataset = MassOutput,
         bestmodel = MassSingle$BestModel, 
         bestmodeldata = MassSingle$BestModelData)


## ----fig.width = 10, fig.height = 7.5-----------------------------------------

plotall(dataset = MassOutput,
        datasetrand = MassRand,
        bestmodel = MassSingle$BestModel, 
        bestmodeldata = MassSingle$BestModelData)


## ----eval = FALSE-------------------------------------------------------------
# 
# MassWin2 <- slidingwin(xvar = list(Temp = MassClimate$Temp),
#                        cdate = MassClimate$Date,
#                        bdate = Mass$Date,
#                        baseline = lm(Mass ~ 1, data = Mass),
#                        cinterval = "day",
#                        range = c(150, 0),
#                        type = "absolute", refday = c(20, 5),
#                        stat = c("max", "mean"),
#                        func = c("lin", "quad"))
# 

## ----eval = FALSE-------------------------------------------------------------
# 
# MassWin2$combos
# 

## ----eval = FALSE-------------------------------------------------------------
# 
# MassWin2[[3]]$BestModel
# 

## ----eval = FALSE-------------------------------------------------------------
# Call:
# lm(formula = Yvar ~ climate + I(climate^2), data = modeldat)
# 
# Coefficients:
#  (Intercept)       climate  I(climate^2)
#    139.39170      -1.33767       0.03332