bobolafrite - 1 year ago 95

R Question

I'm working on an app to analyze time series with R and shiny, and I would like to plot a specific graphic to help choosing between additive or multiplicative model :1

I would like to plot my time series, but also plot two lines which are closest to each maximum and each minimum of each period respectively.

Here is a link to the graphic I would like to draw : https://i.imgsafe.org/fdb95a34f9.png

For the moment here is my code, I called my function

`plot_band`

`plot_band <- function(Xt, period){`

# Create an index

index <- 1:lenght(Xt)

# Create the vector period which value is the period the point belong to

periods <- index%/%period + 1

# Create a dataframe

df <- data.frame(xt= Xt,periods = as.factor(periods))

# FInd the minimums and maximums

mins <- df[df$xt == ave(df$xt, df$period, FUN=min), ]

maxs <- df[df$xt == ave(df$xt, df$period, FUN=max), ]

# Regression with lm

mins_reg <- lm(mins$xt ~ mins$index)

maxs_reg <- lm(maxs$xt ~ maxs$index)

#And I don't know how to plot everything

my_graph <- ggplot(data=df,

Another issue is that

`xt`

`N`

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Answer Source

I finally found a solution for this problem, it might not be the better but here it is :

```
plot_bande <- function(xt,period){
begin <- start(xt)[1]
end <- end(xt)[1]
freq <- frequency(xt)
idx <- seq(begin,end,freq)
periods <- idx %/% period + 1 - idx[1] %/% period
df <- data.frame(data=xt,period=periods, idx=idx)
df$period <- as.factor(df$period)
min <- df[df$data == ave(df$data, df$period, FUN=min), ]
max <- df[df$data == ave(df$data, df$period, FUN=max), ]
reg_min <- lm(min$data ~ min$idx)
reg_max <- lm(max$data ~ max$idx)
a_min <- coef(reg_min)[1]
b_min <- coef(reg_min)[2]
a_max <- coef(reg_max)[1]
b_max <- coef(reg_max)[2]
plot(df$data)
abline(a=a_min,b=b_min,col='blue')
abline(a=a_max,b=b_max,col='red')
legend('topleft', legend=c('Minimum values', 'Maximum values'),col=c('blue','red'), lty=1)
```

}

And you can see the graph I obtained with the sunspot.year dataset and a period of 12 years by clicking this link

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