Man pages for SMAC-Group/wv
Wavelet Variance

ACFAuto-Covariance and Correlation Functions
acf_sumHelper Function for ARMA to WV Approximation
ar1_to_wvAR(1) process to WV
arma11_to_wvARMA(1,1) to WV
ARMAacf_cppCompute Theoretical ACF for an ARMA Process
ARMAtoMA_cppConverting an ARMA Process to an Infinite MA Process
arma_to_wvARMA process to WV
arma_to_wv_appARMA process to WV Approximation
av_ar1Calculate Theoretical Allan Variance for Stationary...
av_wnCalculate Theoretical Allan Variance for Stationary White...
batch_modwt_wvar_cppComputes the MO/DWT wavelet variance for multiple processes
cfilterTime Series Convolution Filters
ci_eta3Generate eta3 confidence interval
ci_eta3_robustGenerate eta3 robust confidence interval
ci_wave_varianceGenerate a Confidence interval for a Univariate Time Series
compare_wvarComparison Between Multiple Wavelet Variances
compare_wvar_no_splitCombined Plot Comparison Between Multiple Wavelet Variances
compare_wvar_splitMulti-Plot Comparison Between Multiple Wavelet Variances
create_wvarCreate a 'wvar' object
decomp_theoretical_wvEach Models Process Decomposed to WV
decomp_to_theo_wvDecomposed WV to Single WV
dft_acfDiscrete Fourier Transformation for Autocovariance Function
diff_cppLagged Differences in Armadillo
diff_invDiscrete Intergral: Inverse Difference
dot-acfAuto-Covariance and Correlation Functions
dr_to_wvDrift to WV
dwtDiscrete Wavelet Transform
dwt_cppDiscrete Wavelet Transform
ma1_to_wvMoving Average Order 1 (MA(1)) to WV
mean_diffMean of the First Difference of the Data
modwtMaximum Overlap Discrete Wavelet Transform
modwt_cppMaximum Overlap Discrete Wavelet Transform
modwt_wvar_cppComputes the (MODWT) wavelet variance
num_repReplicate a Vector of Elements n times
plot.ACFAuto-Covariance and Correlation Functions
plot.dwtPlot Discrete Wavelet Transform
plot.modwtPlot Maximum Overlap Discrete Wavelet Transform
plot.wccv_pairPlot Cross Covariance Pair
plot.wvarPlot Wavelet Variances
print.dwtPrint Discrete Wavelet Transform
print.modwtPrint Maximum Overlap Discrete Wavelet Transform
print.wvarPrint Wavelet Variances
qn_to_wvQuantisation Noise (QN) to WV
quantile_cppFind Quantiles
rfilterTime Series Recursive Filters
robust_edaComparison between classical and robust Wavelet Variances
rw_to_wvRandom Walk to WV
sarma_calculate_spaddingCalculates Length of Seasonal Padding
sarma_componentsDetermine parameter expansion based upon objdesc
sarma_expandExpand Parameters for an SARMA object
sarma_expand_unguided(Internal) Expand the SARMA Parameters
sarma_objdescCreate the ts.model obj.desc given split values
sarma_params_constructEfficient way to merge items together
scales_cppComputes the MODWT scales
seq_cppGenerate a sequence of values
seq_len_cppGenerate a sequence of values based on supplied number
sp_hfilterHaar filter for a spatial case
sp_modwt_cppCompute the Spatial Wavelet Coefficients
summary.dwtSummary Discrete Wavelet Transform
summary.modwtSummary Maximum Overlap Discrete Wavelet Transform
summary.wvarSummary of Wavelet Variances
theoretical_wvModel Process to WV
unitConversionConvert Unit of Time Series Data
wave_varianceGenerate a Wave Variance for a Univariate Time Series
wccvCross Covariance of Matrix
wccv_get_yMapping to log10 scale
wccv_pairCross Covariance of a TS Pair
wn_to_wvGaussian White Noise to WV
wvwv
wvarWavelet Variance
wvar_cppComputes the (MODWT) wavelet variance
SMAC-Group/wv documentation built on May 5, 2019, 6:57 p.m.