PINE LIBRARY
CyberRegimeLib

CyberRegimeLib - online sssm
GaussianRegime parameter/state UDT
PosteriorHistory ring-buffer UDT
Gaussian cloning and prior-stat capping
Online EM accumulation and M-step
Hamilton forward filtering
One-step smoothing
Fixed-horizon Kim smoothing
Active-state hysteresis
Library "CyberRegimeLib"
f_regime_new(dimensions)
Parameters:
dimensions (int)
method clone(source)
Namespace types: GaussianRegime
Parameters:
source (GaussianRegime)
f_clone_regimes(source)
Parameters:
source (array<GaussianRegime>)
f_n_eff_at(regimes, index)
Parameters:
regimes (array<GaussianRegime>)
index (int)
f_cap_prior_stats(regimes, total_cap)
Parameters:
regimes (array<GaussianRegime>)
total_cap (float)
method initialize_stats(regime, regime_count, active_dims)
Namespace types: GaussianRegime
Parameters:
regime (GaussianRegime)
regime_count (int)
active_dims (array<bool>)
f_accumulate_stats(regimes, responsibilities, observation, lambda_eff, admission_weight, count, prior_weighted, full_cov_dims)
Parameters:
regimes (array<GaussianRegime>)
responsibilities (array<float>)
observation (array<float>)
lambda_eff (float)
admission_weight (float)
count (int)
prior_weighted (bool)
full_cov_dims (int)
method mstep(regime, active_dims, ridge_main, ridge_aux, shrinkage, min_n_eff, anchor)
Namespace types: GaussianRegime
Parameters:
regime (GaussianRegime)
active_dims (array<bool>)
ridge_main (float)
ridge_aux (float)
shrinkage (float)
min_n_eff (float)
anchor (float)
f_hamilton_step(transition, filtered, log_likelihoods, count)
Parameters:
transition (matrix<float>)
filtered (array<float>)
log_likelihoods (array<float>)
count (int)
f_history_new(capacity, state_count)
Parameters:
capacity (int)
state_count (int)
method push(history, filtered, predicted)
Namespace types: PosteriorHistory
Parameters:
history (PosteriorHistory)
filtered (array<float>)
predicted (array<float>)
method smooth_one(history, transition, fallback_index, fallback_probability)
Namespace types: PosteriorHistory
Parameters:
history (PosteriorHistory)
transition (matrix<float>)
fallback_index (int)
fallback_probability (float)
method smooth_fixed(history, transition, horizon)
Namespace types: PosteriorHistory
Parameters:
history (PosteriorHistory)
transition (matrix<float>)
horizon (int)
f_hysteresis_state(current, active_since, candidate, best, second, minimum_margin, minimum_bars, current_bar)
Parameters:
current (int)
active_since (int)
candidate (int)
best (float)
second (float)
minimum_margin (float)
minimum_bars (int)
current_bar (int)
GaussianRegime
Fields:
mu (array<float>)
mu_seed (array<float>)
Sigma (matrix<float>)
Sigma_inv (matrix<float>)
F (matrix<float>)
Q_diag (array<float>)
prior (series float)
n_eff (series float)
sum_x (array<float>)
sum_xx (matrix<float>)
PosteriorHistory
Fields:
filtered_flat (array<float>)
predicted_flat (array<float>)
write_idx (series int)
count (series int)
capacity (series int)
state_count (series int)
GaussianRegime parameter/state UDT
PosteriorHistory ring-buffer UDT
Gaussian cloning and prior-stat capping
Online EM accumulation and M-step
Hamilton forward filtering
One-step smoothing
Fixed-horizon Kim smoothing
Active-state hysteresis
Library "CyberRegimeLib"
f_regime_new(dimensions)
Parameters:
dimensions (int)
method clone(source)
Namespace types: GaussianRegime
Parameters:
source (GaussianRegime)
f_clone_regimes(source)
Parameters:
source (array<GaussianRegime>)
f_n_eff_at(regimes, index)
Parameters:
regimes (array<GaussianRegime>)
index (int)
f_cap_prior_stats(regimes, total_cap)
Parameters:
regimes (array<GaussianRegime>)
total_cap (float)
method initialize_stats(regime, regime_count, active_dims)
Namespace types: GaussianRegime
Parameters:
regime (GaussianRegime)
regime_count (int)
active_dims (array<bool>)
f_accumulate_stats(regimes, responsibilities, observation, lambda_eff, admission_weight, count, prior_weighted, full_cov_dims)
Parameters:
regimes (array<GaussianRegime>)
responsibilities (array<float>)
observation (array<float>)
lambda_eff (float)
admission_weight (float)
count (int)
prior_weighted (bool)
full_cov_dims (int)
method mstep(regime, active_dims, ridge_main, ridge_aux, shrinkage, min_n_eff, anchor)
Namespace types: GaussianRegime
Parameters:
regime (GaussianRegime)
active_dims (array<bool>)
ridge_main (float)
ridge_aux (float)
shrinkage (float)
min_n_eff (float)
anchor (float)
f_hamilton_step(transition, filtered, log_likelihoods, count)
Parameters:
transition (matrix<float>)
filtered (array<float>)
log_likelihoods (array<float>)
count (int)
f_history_new(capacity, state_count)
Parameters:
capacity (int)
state_count (int)
method push(history, filtered, predicted)
Namespace types: PosteriorHistory
Parameters:
history (PosteriorHistory)
filtered (array<float>)
predicted (array<float>)
method smooth_one(history, transition, fallback_index, fallback_probability)
Namespace types: PosteriorHistory
Parameters:
history (PosteriorHistory)
transition (matrix<float>)
fallback_index (int)
fallback_probability (float)
method smooth_fixed(history, transition, horizon)
Namespace types: PosteriorHistory
Parameters:
history (PosteriorHistory)
transition (matrix<float>)
horizon (int)
f_hysteresis_state(current, active_since, candidate, best, second, minimum_margin, minimum_bars, current_bar)
Parameters:
current (int)
active_since (int)
candidate (int)
best (float)
second (float)
minimum_margin (float)
minimum_bars (int)
current_bar (int)
GaussianRegime
Fields:
mu (array<float>)
mu_seed (array<float>)
Sigma (matrix<float>)
Sigma_inv (matrix<float>)
F (matrix<float>)
Q_diag (array<float>)
prior (series float)
n_eff (series float)
sum_x (array<float>)
sum_xx (matrix<float>)
PosteriorHistory
Fields:
filtered_flat (array<float>)
predicted_flat (array<float>)
write_idx (series int)
count (series int)
capacity (series int)
state_count (series int)
Bibliothèque Pine
Dans l'esprit TradingView, l'auteur a publié ce code Pine sous forme de bibliothèque open source afin que d'autres programmeurs Pine de notre communauté puissent le réutiliser. Bravo à l'auteur! Vous pouvez utiliser cette bibliothèque à titre privé ou dans d'autres publications open source, mais la réutilisation de ce code dans des publications est régie par nos Règles.
Clause de non-responsabilité
Les informations et publications ne sont pas destinées à être, et ne constituent pas, des conseils ou recommandations financiers, d'investissement, de trading ou autres fournis ou approuvés par TradingView. Pour en savoir plus, consultez les Conditions d'utilisation.
Bibliothèque Pine
Dans l'esprit TradingView, l'auteur a publié ce code Pine sous forme de bibliothèque open source afin que d'autres programmeurs Pine de notre communauté puissent le réutiliser. Bravo à l'auteur! Vous pouvez utiliser cette bibliothèque à titre privé ou dans d'autres publications open source, mais la réutilisation de ce code dans des publications est régie par nos Règles.
Clause de non-responsabilité
Les informations et publications ne sont pas destinées à être, et ne constituent pas, des conseils ou recommandations financiers, d'investissement, de trading ou autres fournis ou approuvés par TradingView. Pour en savoir plus, consultez les Conditions d'utilisation.