oves function

Occurrence part of Vector State Space

Function calculates the probability for the occurrence part of vector state space model. This is needed in order to forecast intermittent demand using other functions.

oves(data, occurrence = c("logistic", "none", "fixed"), ic = c("AICc",
  "AIC", "BIC", "BICc"), h = 10, holdout = FALSE,
  probability = c("dependent", "independent"), model = "ANN",
  persistence = NULL, transition = NULL, phi = NULL, initial = NULL,
  initialSeason = NULL, xreg = NULL, ...)

Arguments

• data: The matrix with data, where series are in columns and observations are in rows.

• occurrence: Type of method used in probability estimation. Can be "none" - none, "fixed" - constant probability or "logistic" - probability based on logit model.

• ic: Information criteria to use in case of model selection.

• h: Forecast horizon.

• holdout: If TRUE, holdout sample of size h is taken from the end of the data.

• probability: Type of probability assumed in the model. If "dependent", then it is assumed that occurrence of one variable is connected with the occurrence with another one. In case of "independent"

  the occurrence of the variables is assumed to happen independent of each other.

• model: Type of ETS model used for the estimation. Normally this should be either "ANN" or "MNN". If you assume that there are some tendencies in occurrence, then you can use more complicated models. Model selection is not yet available.

• persistence: Persistence matrix type. If NULL, then it is estimated. See ves for the details.

• transition: Transition matrix type. If NULL, then it is estimated. See ves for the details.

• phi: Damping parameter type. If NULL, then it is estimated. See ves for the details.

• initial: Initial vector type. If NULL, then it is estimated. See ves for the details.

• initialSeason: Type of the initial vector of seasonal components. If NULL, then it is estimated. See ves for the details.

• xreg: Vector of matrix of exogenous variables, explaining some parts of occurrence variable (probability).

• ...: Other parameters. This is not needed for now.

Returns

The object of class "oves" is returned. It contains following list of values:

• model - the type of the estimated ETS model;
• fitted - fitted values of the constructed model;
• forecast - forecast for h observations ahead;
• states - values of states (currently level only);
• variance - conditional variance of the forecast;
• logLik - likelihood value for the model
• nParam - number of parameters used in the model;
• residuals - residuals of the model;
• data - actual values of probabilities (zeros and ones).
• persistence - the vector of smoothing parameters;
• initial - initial values of the state vector;
• initialSeason - the matrix of initials seasonal states;
• occurrence - type of occurrence model used;
• probability - type of probability used;
• issModel - intermittent state-space model used for calculations. Useful only in the case of occurrence="l" and probability="d".

Details

The function estimates probability of demand occurrence, using one of the VES state-space models.

Examples

Y <- cbind(c(rpois(25,0.1),rpois(25,0.5),rpois(25,1),rpois(25,5)),
           c(rpois(25,0.1),rpois(25,0.5),rpois(25,1),rpois(25,5)))

oves(Y, occurrence="l")
oves(Y, occurrence="l", probability="i")

See Also

oes, ves

Author(s)

Ivan Svetunkov, ivan@svetunkov.com