ACF | Auto-Covariance and Correlation Functions |
acf_sum | Helper Function for ARMA to WV Approximation |
addSpaceIfDuplicate | Add Space to Avoid Duplicate Elements |
addUnits | Add Units to Sensor |
all_bootstrapper | Bootstrap for Everything! |
AR | Create an Autoregressive P [AR(P)] Process |
AR1 | Create an Autoregressive 1 [AR(1)] Process |
ar1_draw | Randomly guess starting parameters for AR1 |
ar1_to_gm | Transform AR1 to GM |
ar1_to_wv | AR(1) process to WV |
ARIMA | Create an Autoregressive Integrated Moving Average (ARIMA)... |
ARMA | Create an Autoregressive Moving Average (ARMA) Process |
ARMA11 | Create an Autoregressive Order 1 - Moving Average Order 1... |
arma11_to_wv | ARMA(1,1) to WV |
ARMAacf_cpp | Compute Theoretical ACF for an ARMA Process |
arma_adapter | ARMA Adapter to ARMA to WV Process function |
arma_draws | Randomly guess starting parameters for ARMA |
ARMAtoMA_cpp | Converting an ARMA Process to an Infinite MA Process |
arma_to_wv | ARMA process to WV |
arma_to_wv_app | ARMA process to WV Approximation |
autofill | Autofill A Vector |
auto_imu | Automatically select appropriate model for IMU |
auto_imu_cpp | Find the auto imu result |
autoplot.auto.imu | Automatic Model Selection Results of IMU Object |
autoplot.auto.imu1 | Automatic Model Selection Results of IMU Object without... |
autoplot.auto.imu2 | Automatic Model Selection Results of IMU Object with... |
autoplot.avar | Graph Allan Variance |
autoplot.gmwm | Graph Solution of the Generalized Method of Wavelet Moments |
autoplot.gmwm1 | Graph Solution of the Generalized Method of Wavelet Moments... |
autoplot.gmwm2 | Graph Solution of the Generalized Method of Wavelet Moments... |
autoplot.gts | Plot Time Series Data |
autoplot.hadam | Graph Hadamard Variance |
autoplot.imu2 | Plot the Wavelet Variances of IMU Object in Combined Type |
autoplot.imu6 | Plot the Wavelet Variances of IMU Object in Split Type |
autoplot.lts | Plot the Latent Time Series Graph |
autoplot.wvar | Graph Wavelet Variances |
autoplot.wvarComp | Detail Implementation to Compare Wavelet Variances |
autoplot.wvar.imu | Plot the Wavelet Variances of IMU Object |
avar | Calculate the Allan Variance |
avar_mo_cpp | Compute Maximal-Overlap Allan Variance using Means |
avar_to_cpp | Compute Tau-Overlap Allan Variance |
batch_modwt_wvar_cpp | Computes the MO/DWT wavelet variance for multiple processes |
bl14_filter | bl14 filter construction |
bl20_filter | bl20 filter construction |
B_matrix | B Matrix |
boot_pval_gof | Generate the Confidence Interval for GOF Bootstrapped |
bootstrap_gof_test | Compute the Bootstrapped GoF Test |
brickwall | Brickwall functionality for MO/DWT Removes boundary... |
brick_wall | Removal of Boundary Wavelet Coefficients |
build_model_set | Build List of Unique Models |
calculate_psi_matrix | Calculate the Psi matrix |
cfilter | Time Series Convolution Filters |
checkEquality | Check Equal Attributes in a GMWM List |
checkParams | Check the Parameters |
ci_eta3 | Generate eta3 confidence interval |
ci_eta3_robust | Generate eta3 robust confidence interval |
ci_wave_variance | Generate a Confidence intervval for a Univariate Time Series |
code_zero | Optim loses NaN |
comb.mat | Create Combination Matrix |
compare_eff | Graphically Compare Classical with Robust GMWM Models |
compare_models | Graphically Compare GMWM Model Fit |
compare_wvar | Compare Wavelet Variances |
compare_wvar.imu | Compare Wavelet Variances for 'imu' Object |
compute_cov_cpp | Computes the (MODWT) wavelet covariance matrix |
count_models | Count Models |
cov_bootstrapper | Bootstrap for Matrix V |
create_imu | Internal IMU Object Construction |
create_wvar | Create a 'wvar' object |
cust.model.score | Formats the model score matrix |
d16_filter | d16 filter construction |
d4_filter | d4 filter construction |
d6_filter | d6 filter construction |
d8_filter | d8 filter construction |
decomp_theoretical_wv | Each Models Process Decomposed to WV |
decomp_to_theo_wv | Decomposed WV to Single WV |
demo_lts | Generate a Demo about the Latent Time Series |
deriv_2nd_ar1 | Analytic second derivative matrix for AR(1) process |
deriv_2nd_arma11 | Analytic D matrix for ARMA(1,1) process |
deriv_2nd_dr | Analytic second derivative matrix for drift process |
deriv_2nd_ma1 | Analytic second derivative for MA(1) process |
deriv_ar1 | Analytic D matrix for AR(1) process |
deriv_arma11 | Analytic D matrix for ARMA(1,1) process |
derivative_first_matrix | Analytic D matrix of Processes |
deriv_dr | Analytic D matrix for Drift (DR) Process |
deriv_ma1 | Analytic D matrix for MA(1) process |
deriv_qn | Analytic D matrix for Quantization Noise (QN) Process |
deriv_rw | Analytic D matrix Random Walk (RW) Process |
deriv_wn | Analytic D Matrix for a Gaussian White Noise (WN) Process |
desc.to.ts.model | Create a ts.model from desc string |
dft_acf | Discrete Fourier Transformation for Autocovariance Function |
diff_cpp | Lagged Differences in Armadillo |
diff_inv | Discrete Intergral: Inverse Difference |
D_matrix | Analytic D matrix of Processes |
do_polyroot_arma | Root Finding C++ |
do_polyroot_cpp | Root Finding C++ |
dot-acf | Auto-Covariance and Correlation Functions |
DR | Create an Drift (DR) Process |
dr_to_wv | Drift to WV |
dwt | Discrete Wavelet Transform |
dwt_cpp | Discrete Wavelet Transform |
e_drift | Expected value DR |
fast_cov_cpp | Computes the (MODWT) wavelet covariance matrix using... |
field_to_matrix | Transform an Armadillo field<vec> to a matrix |
find_full_model | Find the Common Denominator of the Models |
fk14_filter | fk14 filter construction |
fk22_filter | fk22 filter construction |
fk4_filter | fk4 filter construction |
fk6_filter | fk6 filter construction |
fk8_filter | fk8 filter construction |
format_ci | Format the Confidence Interval for Estimates |
formatRobustEff | Get the Computation Method and Efficiency of 'gmwm' Object |
gen_ar1 | Generate an Autoregressive Order 1 ( AR(1) ) sequence |
gen_arima | Generate Autoregressive Order p, Integrated d, Moving Average... |
gen_arma | Generate Autoregressive Order p - Moving Average Order q... |
gen_arma11 | Generate an ARMA(1,1) sequence |
gen_dr | Generate a Drift Process |
gen_generic_sarima | Generate Generic Seasonal Autoregressive Order P - Moving... |
gen_gts | Create a GMWM TS Object based on model |
gen_lts | Generate Latent Time Series Object Based on Model |
gen_lts_cpp | Generate Latent Time Series based on Model (Internal) |
gen_ma1 | Generate an Moving Average Order 1 (MA(1)) Process |
gen_model | Generate Time Series based on Model (Internal) |
gen_qn | Generate a Quantisation Noise (QN) or Rounding Error Sequence |
gen_rw | Generate a Random Walk without Drift |
gen_sarima | Generate Seasonal Autoregressive Order P - Moving Average... |
gen_sarma | Generate Seasonal Autoregressive Order P - Moving Average... |
gen_wn | Generate a Gaussian White Noise Process (WN(sigma^2)) |
getColors | Get N Colors |
getEff | Get 'gmwm' Efficiency Values |
getModel.gmwm | Get the model in a 'gmwm' object |
getObjFun | Retrieve GMWM starting value from Yannick's objective... |
getObjFunStarting | Retrieve GMWM starting value from Yannick's objective... |
get_summary | Routing function for summary info |
ggColor | Emulate ggplot2 default color palette |
GM | Create a Gauss-Markov (GM) Process |
gm_conv | GM Conversion |
gm_to_ar1 | Transform GM to AR1 |
gmwm | Generalized Method of Wavelet Moments (GMWM) for IMUs, ARMA,... |
gmwm-defunct | Defunct function(s) in the gmwm package |
gmwm_engine | Engine for obtaining the GMWM Estimator |
gmwm_imu | GMWM for (Robust) Inertial Measurement Units (IMUs) |
gmwm_master_cpp | Master Wrapper for the GMWM Estimator |
gmwm-package | Generalized Method of Wavelet Moments (GMWM) Package |
gmwm_param_bootstrapper | Bootstrap for Estimating Both Theta and Theta SD |
gmwm_sd_bootstrapper | Bootstrap for Standard Deviations of Theta Estimates |
gmwm_update_cpp | Update Wrapper for the GMWM Estimator |
gof_test | Compute the GOF Test |
graphingVar | Graphical Function for Allan Variance, Wavelet Variance and... |
gts | Create a GMWM TS Object based on data |
guess_initial | Randomly guess a starting parameter |
guess_initial_old | Randomly guess a starting parameter |
haar_filter | Haar filter construction |
hadam | Calculate the Hadamard Variance |
hadam_mo_cpp | Compute Maximal-Overlap Hadamard Variance using Means |
hadam_to_cpp | Compute Tau-Overlap Hadamard Variance |
has | Obtain the value of an object's properties |
idf_arma | Indirect Inference for ARMA |
idf_arma_total | Indirect Inference for ARMA |
imu | Create an IMU Object |
imu_time | Pulls the IMU time from the IMU object |
invert_check | Check Invertibility Conditions |
is_func | Is GMWM Object |
is.validCompEffObj | Validity of the Object List for 'compare.eff' |
is.whole | Integer Check |
is.wholenumber | Check Integer Values |
jacobian_arma | Calculates the Jacobian for the ARMA process |
la16_filter | la16 filter construction |
la20_filter | la20 filter construction |
la8_filter | la8 filter construction |
lm_arma | MLR in Armadillo |
lm_dr | Linear Regression with Drift |
logit | Logit Function |
logit2 | Logit2 Function |
logit2_inv | Logit2 Inverse Function |
logit_inv | Logit Inverse Function |
lts | Generate Latent Time Series Object Based on Data |
m2_drift | Second moment DR |
MA | Create an Moving Average Q [MA(Q)] Process |
MA1 | Create an Moving Average 1 [MA(1)] Process |
ma1_to_wv | Moving Average Order 1 (MA(1)) to WV |
mb16_filter | mb16 filter construction |
mb24_filter | mb24 filter construction |
mb4_filter | mb4 filter construction |
mb8_filter | mb8 filter construction |
mean_diff | Mean of the First Difference of the Data |
minroot | Obtain the smallest polynomial root |
Mod_cpp | Absolute Value or Modulus of a Complex Number. |
model_objdesc | Generate the ts model object description |
model_process_desc | Generate the ts model object's process desc |
model_score | Model Score |
model_theta | Generate the ts model object's theta vector |
Mod_squared_cpp | Absolute Value or Modulus of a Complex Number Squared. |
modwt | Maximum Overlap Discrete Wavelet Transform Calculation of the... |
modwt_cpp | Maximum Overlap Discrete Wavelet Transform |
modwt_wvar_cpp | Computes the (MODWT) wavelet variance |
num_rep | Replicate a Vector of Elements n times |
obj_extract | Extract Object |
optimism_bootstrapper | Bootstrap for Optimism |
opt_n_gof_bootstrapper | Bootstrap for Optimism and GoF |
order_AR1s | Order AR1s by size of phi. |
orderModel | Order the Model |
output.format | Formats the rank.models (auto.imu) object |
packageVersionCRAN | Latest Version of Package on CRAN |
paperSetting | Frequent Graph Setting for Paper |
placeLegend | Place Legend |
plot.ACF | Auto-Covariance and Correlation Functions |
plot.auto.imu | Wrapper to Automatic Model Selection Results of IMU Object |
plot.avar | Wrapper to ggplot Allan Variance Graph |
plot.gmwm | Wrapper to Graph Solution of the Generalized Method of... |
plot.gts | Plot Time Series Data |
plot.hadam | Wrapper to ggplot Hadamard Variance Graph |
plot.lts | Wrapper Function to Plot the Graph of Latent Time Series |
plot.rank.models | Graph 'rank.models' object |
plot.wvar | Wrapper to ggplot Wavelet Variances Graph |
plot.wvar.imu | Wrapper Function to Plot the Wavelet Variances of IMU Object |
plus-.ts.model | Add ts.model objects together |
predict.gmwm | Predict future points in the time series using the solution... |
print.auto.imu | Print function for auto.imu object |
print.avar | Prints Allan Variance |
print_data | Print GMWM Data Object |
print.dwt | Print Discrete Wavelet Transform |
print.gmwm | Print gmwm object |
print.hadam | Prints Hadamard Variance |
print.modwt | Print Maximum Overlap Discrete Wavelet Transform |
print.rank.models | Print function for rank.models object |
print.summary.gmwm | Print summary.gmwm object |
print.ts.model | Multiple a ts.model by constant |
print.wvar | Print Wavelet Variances |
print.wvar.imu | Print Wavelet Variances for 'imu' Object |
print.wvcov | Print Asymptotic Covariance Matrix |
pseudo_logit | Pseudo Logit Function |
pseudo_logit_inv | Pseudo Logit Inverse Function |
qmf | Quadrature Mirror Filter |
QN | Create an Quantisation Noise (QN) Process |
qn_to_wv | Quantisation Noise (QN) to WV |
quantile_cpp | Find Quantiles |
rank_models | Automatically select appropriate model for a set of models |
rank_models_cpp | Find the Rank Models result |
Rcpp_ARIMA | Hook into R's ARIMA function |
read_imu | Read an IMU Binary File into R |
read.imu | Read an IMU Binary File into R |
rev_col_subset | Reverse Subset Column |
reverse_vec | Reverse Armadillo Vector |
rev_row_subset | Reverse Subset Row |
rfilter | Time Series Recursive Filters |
rgmwm | GMWM for Robust/Classical Comparison |
rtruncated_normal | Truncated Normal Distribution Sampling Algorithm |
RW | Create an Random Walk (RW) Process |
rw_to_wv | Random Walk to WV |
SARIMA | Create a Seasonal Autoregressive Integrated Moving Average... |
SARMA | Create a Seasonal Autoregressive Moving Average (SARMA)... |
sarma_calculate_spadding | Calculates Length of Seasonal Padding |
sarma_components | Determine parameter expansion based upon objdesc |
sarma_expand | Expand Parameters for an SARMA object |
sarma_expand_unguided | (Internal) Expand the SARMA Parameters |
sarma_objdesc | Create the ts.model obj.desc given split values |
sarma_params_construct | Efficient way to merge items together |
scales_cpp | Computes the MODWT scales |
select.desc.check | TS Model Checks |
select_filter | Select the Wavelet Filter |
seq_cpp | Generate a sequence of values |
seq_len_cpp | Generate a sequence of values based on supplied number |
set_seed | Set the RNG Seed from within Rcpp |
sort_mat | Sort Matrix by Column |
sub-.imu | Subset an IMU Object |
sum_field_vec | Accumulation of Armadillo field<vec> |
summary.auto.imu | Summary function for auto.imu object |
summary.avar | Summary Allan Variance |
summary.dwt | Summary Discrete Wavelet Transform |
summary.gmwm | Summary of GMWM object |
summary.hadam | Summary Hadamard Variance |
summary.modwt | Summary Maximum Overlap Discrete Wavelet Transform |
summary.rank.models | Summary function for rank.models object |
summary.wvar | Summary of Wavelet Variances |
summary.wvar.imu | Summary of Wavelet Variances for 'imu' Object |
summary.wvcov | Summary Wavelet Covariance Matrix |
theoretical_wv | Model Process to WV |
theta_ci | Generate the Confidence Interval for Theta Estimates |
times-.ts.model | Multiple a ts.model by constant |
transform_values | Transform Values for Optimization |
unitConversion | Convert Unit of Time Series Data |
untransform_values | Revert Transform Values for Display |
update.gmwm | Update (Robust) GMWM object for IMU or SSM |
update.lts | Update Object Attribute |
update_obj | Update the Attributes of Objects |
value | Obtain the value of an object's properties |
var_drift | Variance DR |
vector_to_set | Conversion function of Vector to Set |
w4_filter | w4 filter construction |
wave_variance | Generate a Wave Variance for a Univariate Time Series |
WN | Create an White Noise (WN) Process |
wn_to_wv | Gaussian White Noise to WV |
wvar | Wavelet Variance |
wvar_cpp | Computes the (MODWT) wavelet variance |
wvcov | Calculate the Asymptotic Covariance Matrix |
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