Package index • rjd3filters

Create Specific Moving Averages

dfa_filter(): Direct Filter Approach

fst_filter(): Estimation of a filter using the Fidelity-Smoothness-Timeliness criteria

localpolynomials(): Apply Local Polynomials Filters

lp_filter(): Local Polynomials Filters

simple_ma(): Simple Moving Average

rkhs_filter(): Reproducing Kernel Hilbert Space (RKHS) Filters

rkhs_kernel(): Get RKHS kernel function

rkhs_optimal_bw(): Optimal Bandwith of Reproducing Kernel Hilbert Space (RKHS) Filters

rkhs_optimization_fun(): Optimization Function of Reproducing Kernel Hilbert Space (RKHS) Filters

get_kernel(): Get the coefficients of a kernel

mmsre_filter(): Mean Square Revision Error (mmsre) filter

Stastics on Moving Averages and estimates

cve() cv() loocve() rt() cp(): Diagnostics and goodness of fit of filtered series

diagnostic_matrix(): Compute quality criteria for asymmetric filters

fst(): FST criteria

implicit_forecasts(): Retrieve implicit forecasts corresponding to the asymmetric filters

underlying_forecasts(): Retrieve underlying forecasts corresponding to the asymmetric filters

get_properties_function(): Get properties of filters

mse(): Accuracy/smoothness/timeliness criteria through spectral decomposition

var_estimator(): Variance Estimator

df_var(): Compute the degrees of freedom for the variance estimator

confint_filter(): Confidence intervals

polynomial_matrix(): Create polynomial matrix

Manipulation of Moving Averages and Finite Filters

filter(): Linear Filtering on a Time Series

sum(<moving_average>) `[`(<moving_average>,<numeric>) `[`(<moving_average>,<logical>) `[<-`(<moving_average>,<ANY>,<missing>,<numeric>) cbind(<moving_average>) rbind(<moving_average>) `+`(<moving_average>,<moving_average>) `+`(<moving_average>,<numeric>) `+`(<numeric>,<moving_average>) `+`(<moving_average>,<missing>) `-`(<moving_average>,<missing>) `-`(<moving_average>,<moving_average>) `-`(<moving_average>,<numeric>) `-`(<numeric>,<moving_average>) `*`(<moving_average>,<moving_average>) `*`(<moving_average>,<numeric>) `*`(<numeric>,<moving_average>) `*`(<ANY>,<moving_average>) `*`(<moving_average>,<ANY>) `/`(<moving_average>,<numeric>) `^`(<moving_average>,<numeric>) `*`(<finite_filters>,<moving_average>) `*`(<moving_average>,<finite_filters>) `*`(<finite_filters>,<numeric>) `*`(<ANY>,<finite_filters>) `*`(<finite_filters>,<ANY>) `+`(<numeric>,<finite_filters>) `+`(<finite_filters>,<moving_average>) `+`(<moving_average>,<finite_filters>) `+`(<finite_filters>,<missing>) `-`(<finite_filters>,<missing>) `-`(<finite_filters>,<moving_average>) `-`(<moving_average>,<finite_filters>) `-`(<finite_filters>,<numeric>) `-`(<numeric>,<finite_filters>) `/`(<finite_filters>,<numeric>) `^`(<finite_filters>,<numeric>) `*`(<finite_filters>,<finite_filters>) `+`(<finite_filters>,<finite_filters>) `-`(<finite_filters>,<finite_filters>) `[`(<finite_filters>,<missing>) `[`(<finite_filters>,<ANY>): Operations on Filters

finite_filters() is.finite_filters() show(<finite_filters>): Manipulating Finite Filters

get_moving_average(): Get Moving Averages from ARIMA model

impute_last_obs(): Impute Incomplete Finite Filters

moving_average() is.moving_average() is_symmetric() upper_bound() lower_bound() mirror() rev(<moving_average>) length(<moving_average>) to_seasonal() show(<moving_average>): Manipulation of moving averages

plot_coef() plot_gain() plot_phase(): Plots filters properties

Data

retailsa: Seasonally Adjusted Retail Sales

Deprecated functions

cross_validation() implicit_forecast(): Deprecated function