aidsCalculate: Calculate the demand share equations of a AI or QUAI demand...

In censoredAIDS: Estimation of Censored AI/QUAI Demand System via Maximum Likelihood Estimation (MLE)

Calculate the demand share equations of a AI or QUAI demand system, including demographic variable.

Description

Calculate the demand share equations of a AI or QUAI demand system, including demographic variable.

Usage

aidsCalculate(
  Prices = matrix(),
  Budget = matrix(),
  ShareNames = NULL,
  Demographics = matrix(),
  DemographicNames = NULL,
  Params = matrix(),
  quaids = FALSE
)

Arguments

Prices	A matrix of logged prices with (nxm) dimensions where n is the number of observations and m the number of shares.
Budget	A matrix of logged total expenditure/budget with (nx1) dimensions where n is the number of observations.
ShareNames	A vector of strings containing the share names with (mx1) dimensions where m is the number of shares.
Demographics	A matrix of demographic variables with (nxt) dimensions where n is the number of observations and t the number of demographic variables.
DemographicNames	A vector of strings containing the demographic names with (tx1) dimensions where t is the number of demographic variables.
Params	A vector containing the parameters alpha, beta, gamma, and theta and lambda if elected.
quaids	Logical. Should quadratic form be used instead?

Value

A matrix of estimated shares with (nxm) dimensions where n is the number of observations and m the number of shares.

Examples

## Not run: 
testing_data <- censoredAIDS::MexicanHH_foodConsumption

# Organizing the data for comfort
s1 <- testing_data$s1
s2 <- testing_data$s2
s3 <- testing_data$s3
s4 <- testing_data$s4
s5 <- testing_data$s5
s6 <- testing_data$s6

lnp1 <- testing_data$lnp1
lnp2 <- testing_data$lnp2
lnp3 <- testing_data$lnp3
lnp4 <- testing_data$lnp4
lnp5 <- testing_data$lnp5
lnp6 <- testing_data$lnp6

age <- testing_data$age
size <- testing_data$size
sex <- testing_data$sex
educ <- testing_data$educ

# Alpha
b0 <- rep(0, 5)

# Beta
b0 <- c(b0, rep(0.003, 5))

# Gamma
b0 <- c(b0,0.01,0,0.01,0,0, 0.01,0,0,0,0.01,0,0,0,0,0.01)

# Demos
b0 <- c(b0,rep(0.002, 20))

# Sigma
b0 <- c(b0,1,0,1,0,0,1,0,0,0,1,0,0,0,0,1)

li1 <- censoredaidsLoglike(
  Params = b0,
  Shares = matrix(c(s1, s2, s3, s4, s5, s6), ncol = 6),
  Prices = matrix(c(lnp1, lnp2, lnp3, lnp4, lnp5, lnp6), ncol = 6),
  Budget = matrix(testing_data$lnw),
  Demographics = matrix(c(age, size, educ, sex), ncol = 4),
  quaids = FALSE
)


## End(Not run)

censoredAIDS documentation built on April 12, 2025, 1:53 a.m.