Temporal disaggregation using the model: x(t) = a + b y(t), where x(t) is the indicator, y(t) is the unknown target series, with low-frequency constraints on y.

Temporal disaggregation using the model: x(t) = a + b y(t), where x(t) is the indicator, y(t) is the unknown target series, with low-frequency constraints on y.

Usage

temporaldisaggregationI(
  series,
  indicator,
  conversion = c("Sum", "Average", "Last", "First", "UserDefined"),
  conversion.obsposition = 1,
  rho = 0,
  rho.fixed = FALSE,
  rho.truncated = 0
)

Arguments

series

The time series that will be disaggregated. It must be a ts object.

indicator

High-frequency indicator used in the temporal disaggregation. It must be a ts object.

conversion

Conversion mode (Usually "Sum" or "Average")

conversion.obsposition

Only used with "UserDefined" mode. Position of the observed indicator in the aggregated periods (for instance 7th month of the year)

rho

Only used with Ar1/RwAr1 models. (Initial) value of the parameter

rho.fixed

Fixed rho (T/F, F by default)

rho.truncated

Range for Rho evaluation (in [rho.truncated, 1[)

Value

An object of class "JD3TempDisaggI"

Examples

# retail data, monthly indicator
Y<-rjd3toolkit::aggregate(rjd3toolkit::retail$RetailSalesTotal, 1)
x<-rjd3toolkit::retail$FoodAndBeverageStores
td<-rjd3bench::temporaldisaggregationI(Y, indicator=x)
y<-td$estimation$disagg

# qna data, quarterly indicator
data("qna_data")
Y<-ts(qna_data$B1G_Y_data[,"B1G_CE"], frequency=1, start=c(2009,1))
x<-ts(qna_data$TURN_Q_data[,"TURN_INDEX_CE"], frequency=4, start=c(2009,1))
td<-rjd3bench::temporaldisaggregationI(Y, indicator=x)
a<-td$regression$a
b<-td$regression$b