| CLVTools-package | Customer Lifetime Value Tools |
| 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 |
| 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) |
| 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 |
| fitted.clv.fitted | Extract Unconditional Expectation |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| vcov.clv.fitted | Calculate Variance-Covariance Matrix for CLV Models fitted with Maximum Likelihood Estimation |