R: Tools for Customer Lifetime Value Estimation

# Tools for Customer Lifetime Value Estimation

## Documentation for package ‘CLVTools’ version 0.12.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

A B C F G H L N P S V

CLVTools-package | Customer Lifetime Value Tools

## -- A --

apparelDynCov | Time-varying Covariates for the Apparel Retailer Dataset
apparelDynCovFuture | Future Time-varying Covariates for the Apparel Retailer Dataset
apparelStaticCov | Time-invariant Covariates for the Apparel Retailer Dataset
apparelTrans | Apparel Retailer Dataset
as.clv.data | Coerce to clv.data object
as.clv.data.data.frame | Coerce to clv.data object
as.clv.data.data.table | Coerce to clv.data object
as.data.frame.clv.data | Coerce to a Data Frame
as.data.table.clv.data | Coerce to a Data Table

## -- B --

bgbb | BG/BB models - Work In Progress
bgbb-method | BG/BB models - Work In Progress
bgnbd | BG/NBD models
bgnbd-method | BG/NBD models
bgnbd_CET | BG/NBD: Conditional Expected Transactions
bgnbd_expectation | BG/NBD: Unconditional Expectation
bgnbd_LL | BG/NBD: Log-Likelihood functions
bgnbd_nocov_CET | BG/NBD: Conditional Expected Transactions
bgnbd_nocov_expectation | BG/NBD: Unconditional Expectation
bgnbd_nocov_LL_ind | BG/NBD: Log-Likelihood functions
bgnbd_nocov_LL_sum | BG/NBD: Log-Likelihood functions
bgnbd_nocov_PAlive | BG/NBD: Probability of Being Alive
bgnbd_nocov_PMF | BG/NBD: Probability Mass Function (PMF)
bgnbd_PAlive | BG/NBD: Probability of Being Alive
bgnbd_pmf | BG/NBD: Probability Mass Function (PMF)
bgnbd_staticcov_CET | BG/NBD: Conditional Expected Transactions
bgnbd_staticcov_expectation | BG/NBD: Unconditional Expectation
bgnbd_staticcov_LL_ind | BG/NBD: Log-Likelihood functions
bgnbd_staticcov_LL_sum | BG/NBD: Log-Likelihood functions
bgnbd_staticcov_PAlive | BG/NBD: Probability of Being Alive
bgnbd_staticcov_PMF | BG/NBD: Probability Mass Function (PMF)

## -- C --

cdnow | CDNOW dataset
clv.bootstrapped.apply | Bootstrapping: Fit a model again on sampled data and apply method
clvdata | Create an object for transactional data required to estimate CLV
CLVTools | Customer Lifetime Value Tools

## -- F --

fitted.clv.fitted | Extract Unconditional Expectation

## -- G --

gg | Gamma/Gamma Spending model
gg-method | Gamma/Gamma Spending model
ggomnbd | Gamma-Gompertz/NBD model
ggomnbd-method | Gamma-Gompertz/NBD model
ggomnbd_CET | GGompertz/NBD: Conditional Expected Transactions
ggomnbd_expectation | GGompertz/NBD: Unconditional Expectation
ggomnbd_LL | GGompertz/NBD: Log-Likelihood functions
ggomnbd_nocov_CET | GGompertz/NBD: Conditional Expected Transactions
ggomnbd_nocov_expectation | GGompertz/NBD: Unconditional Expectation
ggomnbd_nocov_LL_ind | GGompertz/NBD: Log-Likelihood functions
ggomnbd_nocov_LL_sum | GGompertz/NBD: Log-Likelihood functions
ggomnbd_nocov_PAlive | GGompertz/NBD: Probability of Being Alive
ggomnbd_nocov_PMF | GGompertz/NBD: Probability Mass Function (PMF)
ggomnbd_PAlive | GGompertz/NBD: Probability of Being Alive
ggomnbd_PMF | GGompertz/NBD: Probability Mass Function (PMF)
ggomnbd_staticcov_CET | GGompertz/NBD: Conditional Expected Transactions
ggomnbd_staticcov_expectation | GGompertz/NBD: Unconditional Expectation
ggomnbd_staticcov_LL_ind | GGompertz/NBD: Log-Likelihood functions
ggomnbd_staticcov_LL_sum | GGompertz/NBD: Log-Likelihood functions
ggomnbd_staticcov_PAlive | GGompertz/NBD: Probability of Being Alive
ggomnbd_staticcov_PMF | GGompertz/NBD: Probability Mass Function (PMF)
gg_LL | Gamma-Gamma: Log-Likelihood Function

## -- H --

hessian | Calculate hessian for a fitted model
hessian-method | Calculate hessian for a fitted model
hessian.clv.fitted | Calculate hessian for a fitted model

## -- L --

latentAttrition | Formula Interface for Latent Attrition Models
lrtest | Likelihood Ratio Test of Nested Models
lrtest-method | Likelihood Ratio Test of Nested Models
lrtest.clv.fitted | Likelihood Ratio Test of Nested Models

## -- N --

newcustomer | New customer prediction data
newcustomer.dynamic | New customer prediction data
newcustomer.spending | New customer prediction data
newcustomer.static | New customer prediction data
nobs.clv.data | Number of observations
nobs.clv.fitted | Number of observations

## -- P --

plot | Plot Diagnostics for a Fitted Transaction Model
plot-method | Plot expected and actual mean spending per transaction
plot-method | Plot Diagnostics for a Fitted Transaction Model
plot.clv.data | Plot Diagnostics for the Transaction data in a clv.data Object
plot.clv.fitted.spending | Plot expected and actual mean spending per transaction
plot.clv.fitted.transactions | Plot Diagnostics for a Fitted Transaction Model
pmf | Probability Mass Function
pmf-method | Probability Mass Function
pnbd | Pareto/NBD models
pnbd-method | Pareto/NBD models
pnbd_CET | Pareto/NBD: Conditional Expected Transactions
pnbd_DERT | Pareto/NBD: Discounted Expected Residual Transactions
pnbd_expectation | Pareto/NBD: Unconditional Expectation
pnbd_LL | Pareto/NBD: Log-Likelihood functions
pnbd_nocov_CET | Pareto/NBD: Conditional Expected Transactions
pnbd_nocov_DERT | Pareto/NBD: Discounted Expected Residual Transactions
pnbd_nocov_expectation | Pareto/NBD: Unconditional Expectation
pnbd_nocov_LL_ind | Pareto/NBD: Log-Likelihood functions
pnbd_nocov_LL_sum | Pareto/NBD: Log-Likelihood functions
pnbd_nocov_PAlive | Pareto/NBD: Probability of Being Alive
pnbd_nocov_PMF | Pareto/NBD: Probability Mass Function (PMF)
pnbd_PAlive | Pareto/NBD: Probability of Being Alive
pnbd_pmf | Pareto/NBD: Probability Mass Function (PMF)
pnbd_staticcov_CET | Pareto/NBD: Conditional Expected Transactions
pnbd_staticcov_DERT | Pareto/NBD: Discounted Expected Residual Transactions
pnbd_staticcov_expectation | Pareto/NBD: Unconditional Expectation
pnbd_staticcov_LL_ind | Pareto/NBD: Log-Likelihood functions
pnbd_staticcov_LL_sum | Pareto/NBD: Log-Likelihood functions
pnbd_staticcov_PAlive | Pareto/NBD: Probability of Being Alive
pnbd_staticcov_PMF | Pareto/NBD: Probability Mass Function (PMF)
predict | Predict CLV from a fitted transaction model
predict-method | Infer customers' spending
predict-method | Predict CLV from a fitted transaction model
predict.clv.fitted.spending | Infer customers' spending
predict.clv.fitted.transactions | Predict CLV from a fitted transaction model
print.summary.clv.fitted | Summarizing a fitted CLV model

## -- S --

SetDynamicCovariates | Add Dynamic Covariates to a CLV data object
SetStaticCovariates | Add Static Covariates to a CLV data object
spending | Formula Interface for Spending Models
subset | Subsetting clv.data
subset.clv.data | Subsetting clv.data
summary.clv.fitted | Summarizing a fitted CLV model
summary.clv.fitted.transactions.static.cov | Summarizing a fitted CLV model

## -- V --

vcov.clv.fitted | Calculate Variance-Covariance Matrix for CLV Models fitted with Maximum Likelihood Estimation