How to select appropriate sin() terms to fit a time series using R-CodePudding

I want to fit a time series with sin() function because it has a form of some periods (crests and troughs). However, for now I only guessed it, e.g., 1 month, two months, ..., 1 year, 2 year. Is there some function in R to estimate the multiple periods in a data series?

Below is an example which I want to fit it using the combination of sin() functions. The expression in lm() is a try after several guesses (red line in the Figure below). How can I find the sin() terms with appropriate periods?

t <- 1:365
y <- c(-1,-1.3,-1.6,-1.8,-2.1,-2.3,-2.5,-2.7,-2.9,-3,-2,-1.1,-0.3,0.5,1.1,1.6,2.1,2.5,2.8,3.1,3.4,3.7,4.2,4.6,5,5.3,5.7,5.9,6.2,5.8,5.4,5,4.6,4.2,3.9,3.6,3.4,3.1,2.9,2.8,2.6,2.5,2.3,1.9,1.5,1.1,0.8,0.5,0.2,0,-0.1,-0.3,-0.4,-0.5,-0.5,-0.6,-0.7,-0.8,-0.9,-0.8,-0.6,-0.3,-0.1,0.1,0.4,0.6,0.9,1.1,1.3,1.5,1.7,2.1,2.4,2.7,3,3.3,3.5,3.8,4.3,4.7,5.1,5.5,5.9,6.2,6.4,6.6,6.7,6.8,6.8,6.9,7,6.9,6.8,6.7,
       6.5,6.4,6.4,6.3,6.2,6,5.9,5.7,5.6,5.5,5.4,5.4,5.1,4.9,4.8,4.6,4.5,4.4,4.3,3.9,3.6,3.3,3,2.8,2.6,2.4,2.6,2.5,2.4,2.3,2.3,2.2,2.2,2.3,2.4,2.4,2.5,2.5,2.6,2.6,2.4,2.1,1.9,1.8,1.6,1.4,1.3,1,0.7,0.5,0.2,0,-0.2,-0.4,-0.2,-0.1,0.1,0.1,0.1,0.1,0.1,0.1,0,0,-0.1,-0.1,-0.2,-0.2,-0.3,-0.3,-0.4,-0.5,-0.5,-0.6,-0.7,-0.7,-0.8,-0.8,-0.8,-0.9,-0.9,-0.9,-1.3,-1.6,-1.9,-2.1,-2.3,-2.6,-2.9,-2.9,-2.9,-2.9,
       -2.9,-3,-3,-3,-2.8,-2.7,-2.5,-2.4,-2.3,-2.2,-2.1,-2,-2,-1.9,-1.9,-1.8,-1.8,-1.8,-1.9,-1.9,-2,-2.1,-2.2,-2.2,-2.3,-2.4,-2.5,-2.6,-2.7,-2.8,-2.9,-2.9,-2.9,-2.9,-2.9,-2.9,-2.9,-2.9,-2.9,-2.9,-2.8,-2.8,-2.7,-2.7,-2.6,-2.6,-2.8,-3,-3.1,-3.3,-3.4,-3.5,-3.6,-3.5,-3.4,-3.3,-3.3,-3.2,-3,-2.9,-2.8,-2.8,-2.7,-2.6,-2.6,-2.6,-2.5,-2.6,-2.7,-2.8,-2.8,-2.9,-3,-3,-3,-3,-2.9,-2.9,-2.9,-2.9,-2.9,-2.8,
       -2.7,-2.6,-2.5,-2.4,-2.3,-2.3,-2.1,-1.9,-1.8,-1.7,-1.5,-1.4,-1.3,-1.5,-1.7,-1.8,-1.9,-2,-2.1,-2.2,-2.4,-2.5,-2.6,-2.7,-2.8,-2.8,-2.9,-3.1,-3.2,-3.3,-3.4,-3.5,-3.5,-3.6,-3.6,-3.5,-3.4,-3.3,-3.2,-3.1,-3,-2.7,-2.3,-2,-1.8,-1.5,-1.3,-1.1,-0.9,-0.7,-0.6,-0.5,-0.3,-0.2,-0.1,-0.3,-0.5,-0.6,-0.7,-0.8,-0.9,-1,-1.1,-1.1,-1.2,-1.2,-1.2,-1.2,-1.2,-0.8,-0.4,-0.1,0.2,0.5,0.8,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.6,0.3,0,-0.2,-0.5,-0.7,-0.8)

dt <- data.frame(t = t, y = y)
plot(x = dt$t, y = dt$y)

lm <- lm(y ~ sin(2*3.1416/365*t) cos(2*3.1416/365*t) 
           sin(2*2*3.1416/365*t) cos(2*2*3.1416/365*t) 
           sin(2*4*3.1416/365*t) cos(2*4*3.1416/365*t) 
           sin(2*5*3.1416/365*t) cos(2*5*3.1416/365*t) 
           sin(2*6*3.1416/365*t) cos(2*6*3.1416/365*t) 
           sin(2*0.5*3.1416/365*t) cos(2*0.5*3.1416/365*t),
         data = dt)

summary(lm)$adj.r.squared
plot(dt$y); lines(predict(lm), type = "l", col = "red")

CodePudding user response：

Following my comment to the question,

In