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CRAFT provides Conditional Regime Analog Forecasting with Trajectories tools for multivariate time series. It builds lag and lead trajectory embeddings, detects SVD-based changepoint regimes, estimates transition probabilities, samples plausible future-trajectory analogues, and fits smooth empirical forecast distributions.
After CRAN release:
install.packages("CRAFT")For local development from this folder:
install.packages(".", repos = NULL, type = "source")library(CRAFT)
set.seed(1)
series <- data.frame(
asset_a = cumprod(1 + rnorm(100, 0.001, 0.01)),
asset_b = cumprod(1 + rnorm(100, 0.0005, 0.012))
)
fit <- craft_fit(
series,
window = 5,
n_draws = 100,
n_factors = 1,
min_segment = 5,
max_regimes_per_factor = 3,
n_testing = 0,
verbose = FALSE
)
fit$valid_joint_acc
pred <- craft_predict(fit, n_draws = 25, seed = 1)
names(pred$return_dists)Lower-level functions are available for custom pipelines:
trajectory_embedding() builds aligned past and future
trajectory matrices.svd_changepoint_regimes() detects regimes in
transformed time-series data.regime_sampler() samples historical future-trajectory
rows from regime probabilities.trajectory_forecast() fits smooth empirical forecast
distributions.denoiser() selects informative numeric features before
regime detection.time_volume_weights() creates volume-derived
observation weights.Before submitting to CRAN, replace the placeholder maintainer email
in DESCRIPTION with the real maintainer email address.
MIT + file LICENSE
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.