PLN_RE: A Poisson Lognormal Model with Random Effects

Description

Estimate a Poisson Lognormal model with random effects in panel counting data. This model accounts for heterogeneity on the individual level, and heterogeneity on the <individual, time> level.

Usage

PLN_RE(formula, id, data = NULL, par = NULL, gamma = 1, max_gamma = 5,
  sigma = 1, max_sigma = 3, method = "BFGS", lower = NULL,
  upper = NULL, H = 20, psnH = 20, accu = 10, reltol = 1e-08,
  verbose = 0, tol_gtHg = Inf)

Value

A list containing the results of the estimated model

Arguments

formula: Formula of the model
id: A vector that represents the identity of individuals, numeric or character
data: Input data, a data frame
par: Starting values for estimates
gamma: Variance of random effects on the <individual, time> level for PLN_RE
max_gamma: Largest allowed initial gamma
sigma: Variance of random effects on the individual level for PLN_RE
max_sigma: Largest allowed initial sigma
method: Searching algorithm, don't change default unless you know what you are doing
lower: Lower bound for estiamtes
upper: Upper bound for estimates
H: A vector of length 2, specifying the number of points for inner and outer Quadratures
psnH: Number of Quadrature points for Poisson RE model
accu: L-BFGS-B only, 1e12 for low accuracy; 1e7 for moderate accuracy; 10.0 for extremely high accuracy. See optim
reltol: Relative convergence tolerance. default typically 1e-8
verbose: Level of output during estimation. Lowest is 0.
tol_gtHg: tolerance on gtHg, not informative for L-BFGS-B

References

1. Jing Peng and Christophe Van den Bulte. Participation vs. Effectiveness of Paid Endorsers in Social Advertising Campaigns: A Field Experiment. Working Paper.

2. Jing Peng and Christophe Van den Bulte. How to Better Target and Incent Paid Endorsers in Social Advertising Campaigns: A Field Experiment. In Proceedings of the 2015 International Conference on Information Systems.

Examples

Run this code

# \donttest{
data(rt)
est = PLN_RE(num.words~fans+tweets+as.factor(tweet.id),
              id=rt$user.id[rt$isRetweet==1],
              data=rt[rt$isRetweet==1,])
# }