UCRCD {DIMORA}R Documentation

UCRCD model

Description

Function that estimates the Unbalanced Competition Regime Change Diachronic model. Fitted values for cumulative and instantaneous data are displayed (if display = T).

Usage

UCRCD(series1, series2, display=T, alpha=0.05,
      delta=0.01, gamma=0.01, par="double",
      m1  = BM(series1,display = F)$Estimate[1,1],
      m2  = BM(series2,display = F)$Estimate[1,1],
      p1c = BM(series1,display = F)$Estimate[2,1],
      q1c = BM(series1,display = F)$Estimate[3,1],
      p2  = BM(series2,display = F)$Estimate[2,1],
      q2  = BM(series2,display = F)$Estimate[3,1])

Arguments

series1

the istantaneous observed data of the first product.

series2

the istantaneous observed data of the second product.

alpha

the significance level for confidence intervals.

par

default is 'double'. Instead 'unique', meaning the costraint delta equal to gamma has been selected.

display

if TRUE returns the predicted values for cumulative and instantaneous observed data.

delta

preliminary estimate of delta.

gamma

preliminary estimate of gamma.

m1

preliminary estimate of the first product's market potential under competition

m2

preliminary estimate of the second product's market potential

p1c

preliminary estimate of the first product's innovation coefficient under competition

p2

preliminary estimate of the second product's innovation coefficient

q1c

preliminary estimate of the first product's imitation coefficient under competition

q2

preliminary estimate of the second product's imitation coefficient

Details

The model estimates several parameters that refer both to the stand-alone phase and the competition phase. The description of the parameters is reported below: (wom = "Word Of Mouth")

Value

UCRCD returns an object of class "Dimora".

The function summary is used to obtain and print a summary table of the results. The generic accessor functions coefficients, fitted and residuals extract various useful features of the value returned by UCRCD.

An object of class "Dimora" is a list containing at least the following components:

model

the model formula used.

type

the model frame used.

Estimate

a summary table of estimates.

coefficients

a named vector of coefficients.

Rsquared

the statistical measure R-squared (on the istantaneous data).

RSS

the residual sum of squares (on the istantaneous data).

residuals

the residuals (observed cumulative data - fitted cumulative data).

fitted

the cumulative fitted values.

data

the cumlative observed data.

call

the matched call.

The UCRCD model is estimated on the instantaneous data. For this reason, the UCRCD function also returns the following elements:

data.i

the instantaneous observed data.

fitted.i

the instantaneous fitted values.

residuals.i

the residuals (observed instantaneous data - fitted instantaneous data).

Author(s)

References

Guidolin, M. (2023). Innovation Diffusion Models: Theory and Practice, First Edition. John Wiley & Sons Ltd.

Guseo, R., & Mortarino, C. (2014). Within-brand and cross-brand word-of-mouth for sequential multi-innovation diffusions. IMA Journal of Management Mathematics, 25(3), 287-311.

See Also

The Dimora models: BM, GBM, GGM.

summary.Dimora for summaries.

plot.Dimora for graphics and residuals analysis.

predict.Dimora for prediction.

make.instantaneous to create instantaneous series from the cumulative one.

Examples

data(DBdimora)
Gd <- DBdimora$Gdenmark[1:36]
Rd <- DBdimora$Rdenmark[13:36]
Ca <- DBdimora$Caustralia
Ra <- DBdimora$Raustralia[26:56]

## Example 1
M8 <- UCRCD(Gd,Rd)
summary(M8)
plot.Dimora(M8,type="fit")

## Example 2
M9 <- UCRCD(Ca,Ra,par = "unique",display=FALSE)
summary(M9)
plot.Dimora(M9)
[Package DIMORA version 0.3.6 Index]