| tidy_fft | R Documentation | 
Perform an fft using stats::fft() and return a tidier style output list with plots.
tidy_fft(
  .data,
  .date_col,
  .value_col,
  .frequency = 12L,
  .harmonics = 1L,
  .upsampling = 10L
)
.data | 
 The data.frame/tibble you will pass for analysis.  | 
.date_col | 
 The column that holds the date.  | 
.value_col | 
 The column that holds the data to be analyzed.  | 
.frequency | 
 The frequency of the data, 12 = monthly for example.  | 
.harmonics | 
 How many harmonic waves do you want to produce.  | 
.upsampling | 
 The up sampling of the time series.  | 
This function will perform a few different things, but primarily it will
compute the Fast Discrete Fourier Transform (FFT) using stats::fft(). The
formula is given as:
y[h] = sum_{k=1}^n z[k]*exp(-2*pi*1i*(k-1)*(h-1)/n)
There are many items returned inside of a list invisibly. There are four primary categories of data returned in the list. Below are the primary categories and the items inside of them.
data:
data
error_data
input_vector
maximum_harmonic_tbl
differenced_value_tbl
dff_tbl
ts_obj
plots:
harmonic_plot
diff_plot
max_har_plot
harmonic_plotly
max_har_plotly
parameters:
harmonics
upsampling
start_date
end_date
freq
model:
m
harmonic_obj
harmonic_model
model_summary
A list object returned invisibly.
Steven P. Sanderson II, MPH
Other Data Generator: 
ts_brownian_motion(),
ts_brownian_motion_augment(),
ts_geometric_brownian_motion(),
ts_geometric_brownian_motion_augment(),
ts_random_walk()
suppressPackageStartupMessages(library(dplyr))
data_tbl <- AirPassengers %>%
  ts_to_tbl() %>%
  select(-index)
a <- tidy_fft(
  .data = data_tbl,
  .value_col = value,
  .date_col = date_col,
  .harmonics = 3,
  .frequency = 12
)
a$plots$max_har_plot
a$plots$harmonic_plot
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