What is the process to obtain the number of local extreme points in a time-series dataset using R?

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1. Load the necessary R packages, such as ‘stats’.
2. Import the time-series data and convert it to a time-series object using the ts() or zoo() function.
3. Smooth the time-series data using functions like the loess() or the smooth.spline() function.
4. Retrieve the local extrema points using functions such as the diff() and sign() functions to calculate the first derivative and changes in the sign of the data, respectively.
5. Count the number of local extreme points using a function like length().

Example code:

# Load packages
library(stats)

# Import and convert data to a time-series object
ts_data <- ts(data, start = c(2010, 1), end = c(2020, 12), frequency = 12)

# Smooth the data
smooth_data <- loess(ts_data ~ time(ts_data))

# Calculate first derivative and change in sign
diff_data <- diff(sign(diff(smooth_data)))

# Count local extreme points
num_extreme_points <- length(which(diff_data < 0))