boiwsa {boiwsa}

Seasonal adjustment of weekly data

Description

Seasonal adjustment of weekly data

Usage

boiwsa(
  x,
  dates,
  r = 0.8,
  auto.ao.seacrh = TRUE,
  out.threshold = 3.8,
  ao.list = NULL,
  my.k_l = NULL,
  H = NULL,
  ic = "aicc",
  method = "additive"
)

Arguments

x

Input time series as a numeric vector

dates

a vector of class "Date", containing the data dates

r

Defines the rate of decay of the weights. Should be between zero and one. By default is set to 0.8.

auto.ao.seacrh

Boolean. Search for additive outliers

out.threshold

t-stat threshold in outlier search. By default is 3.8

ao.list

Vector with user specified additive outliers in a date format

my.k_l

Numeric vector defining the number of yearly and monthly trigonometric variables. If NULL, is found automatically using the information criteria

H

Matrix with holiday- and trading day factors

ic

Information criterion used in the automatic search for the number of trigonometric regressors. There are thee options: aic, aicc and bic. By default uses aicc

method

Decomposition type: additive or multiplicative

Value

sa Seasonally adjusted series

my.k_l Number of trigonometric variables used to model the seasonal pattern

sf Estimated seasonal effects

hol.factors Estimated holiday effects

out.factors Estimated outlier effects

beta Regression coefficients for the last year

m lm object. Unweighted OLS regression on the full sample

Author(s)

Tim Ginker

Examples

 # Not run
 # Seasonal adjustment of weekly US gasoline production
 
 data("gasoline.data")
 res=boiwsa(x=gasoline.data$y,dates=gasoline.data$date)