adj_coexposure          Adjusting for expected changes in co-exposure
                        (TDLMM)
coExp                   Randomly sampled exposure from Colorado
                        counties
combine.models          Combines information from DLMs of single
                        exposure
combine.models.tdlmm    Combines information from DLMs of mixture
                        exposures.
cppIntersection         fast set intersection tool assumes sorted
                        vectors A and B
dlmEst                  Calculates the distributed lag effect with DLM
                        matrix for linear models.
dlmtree                 Fit tree structured distributed lag models
dlmtreeGPFixedGaussian
                        dlmtree model with fixed Gaussian process
                        approach
dlmtreeGPGaussian       dlmtree model with Gaussian process approach
dlmtreeHDLMGaussian     dlmtree model with shared HDLM approach
dlmtreeHDLMMGaussian    dlmtree model with HDLMM approach
dlmtreeTDLMFixedGaussian
                        dlmtree model with fixed Gaussian approach
dlmtreeTDLMNestedGaussian
                        dlmtree model with nested Gaussian approach
dlmtreeTDLM_cpp         dlmtree model with nested HDLM approach
dlnmEst                 Calculates the distributed lag effect with DLM
                        matrix for non-linear models.
dlnmPLEst               Calculates the distributed lag effect with DLM
                        matrix for non-linear models.
drawTree                Draws a new tree structure
estDLM                  Calculates subgroup-specific lag effects for
                        heterogeneous models
exposureCov             Exposure covariance structure
get_sbd_dlmtree         Download simulated data for dlmtree articles
mixEst                  Calculates the lagged interaction effects with
                        MIX matrix for linear models.
monotdlnm_Cpp           dlmtree model with monotone tdlnm approach
pip                     Calculates posterior inclusion probabilities
                        (PIPs) for modifiers in HDLM & HDLMM
plot.summary.monotone   Returns variety of plots for model summary of
                        class 'monotone'
plot.summary.tdlm       Plots a distributed lag function for model
                        summary of 'tdlm'
plot.summary.tdlmm      Plots DLMMs for model summary of class 'tdlmm'
plot.summary.tdlnm      Returns variety of plots for model summary of
                        class 'tdlnm'
pm25Exposures           PM2.5 Exposure data
ppRange                 Makes a 'pretty' output of a group of numbers
predict.hdlm            Calculates predicted response for HDLM
predict.hdlmm           Calculates predicted response for HDLMM
print.hdlm              Print a hdlm Object
print.hdlmm             Print a hdlmm Object
print.monotone          Print a monotone Object
print.summary.hdlm      Prints an overview with summary of model class
                        'hdlm'
print.summary.hdlmm     Prints an overview with summary of model class
                        'hdlmm'
print.summary.monotone
                        Prints an overview with summary of model class
                        'monotone'
print.summary.tdlm      Prints an overview with summary of model class
                        'tdlm'
print.summary.tdlmm     Prints an overview with summary of model class
                        'tdlmm'
print.summary.tdlnm     Prints an overview with summary of model class
                        'tdlnm'
print.tdlm              Print a tdlm Object
print.tdlmm             Print a tdlmm Object
print.tdlnm             Print a tdlnm Object
rcpp_pgdraw             Multiple draw polya gamma latent variable for
                        var c[i] with size b[i]
rtmvnorm                Truncated multivariate normal sampler, mean mu,
                        cov sigma, truncated (0, Inf)
ruleIdx                 Calculates the weights for each modifier rule
scaleModelMatrix        Centers and scales a matrix
shiny                   shiny
shiny.hdlm              Executes a 'shiny' app for HDLM.
shiny.hdlmm             Executes a 'shiny' app for HDLMM.
sim.hdlmm               Creates simulated data for HDLM & HDLMM
sim.tdlmm               Creates simulated data for TDLM & TDLMM
sim.tdlnm               Creates simulated data for TDLNM
splitPIP                Calculates the posterior inclusion probability
                        (PIP).
splitpoints             Determines split points for continuous
                        modifiers
summary.hdlm            Creates a summary object of class 'hdlm'
summary.hdlmm           Creates a summary object of class 'hdlmm'
summary.monotone        Creates a summary object of class 'monotone'
summary.tdlm            Creates a summary object of class 'tdlm'
summary.tdlmm           Creates a summary object of class 'tdlmm'
summary.tdlnm           Creates a summary object of class 'tdlnm'
tdlmm                   Treed Distributed Lag Mixture Models
                        (Deprecated)
tdlmm_Cpp               dlmtree model with tdlmm approach
tdlnm                   Treed Distributed Lag Non-Linear Models
                        (Deprecated)
tdlnm_Cpp               dlmtree model with tdlnm approach
zeroToInfNormCDF        Integrates (0,inf) over multivariate normal
zinbCo                  Time-series exposure data for ZINB simulated
                        data
