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Roadmap
This page tracks functionality that exists in the R greybox package but is
not yet ported (or only partially ported) to the Python package. It is the
single source of truth for "is X available in Python?" — individual pages link
here rather than scattering TBA markers. The authoritative status matrix is on
Home; this page expands on the R-only entries.
Status: R-only = not in Python yet; partial = present in Python but missing
features compared to R.
| Feature | R | Python | Status | Notes |
|---|---|---|---|---|
| Scale (variance) model | sm() |
— | R-only | Dynamic model of the error scale. |
| Bootstrap of coefficients | coefbootstrap() |
— | R-only | |
| Three-parameter lognormal |
dtplnorm() etc. |
— | R-only | Extra distribution family. |
| Feature | R | Python | Status | Notes |
|---|---|---|---|---|
| Regression Model Confidence Bounds test | rmcb() |
— | R-only | Nemenyi/MCB-style comparison of methods. |
| Point information criteria |
pAIC(), pAICc(), pBIC(), pBICc()
|
point_lik() |
partial | Point-wise likelihood is in Python; the per-observation IC wrappers are not. |
| Feature | R | Python | Status | Notes |
|---|---|---|---|---|
| Cramer's V | cramer() |
— | R-only | Association for two categorical variables. See association. |
| Feature | R | Python | Status | Notes |
|---|---|---|---|---|
| Automatic demand identification |
aid(), aidCat()
|
— | R-only | Classifies demand type and flags stockouts. |
| Feature | R | Python | Status | Notes |
|---|---|---|---|---|
| Graph maker | graphmaker() |
— | R-only | Actuals/fitted/forecast plot. |
| Spread plot | spread() |
— | R-only | Scatterplot/boxplot matrix. |
| Table plot | tableplot() |
— | R-only | Two-categorical-variable plot. |
| Feature | R | Python | Status | Notes |
|---|---|---|---|---|
| DST detection | detectdst() |
— | R-only | |
| Leap-year detection | detectleap() |
— | R-only | |
| Polynomial products | polyprod() |
— | R-only | |
| DSR bootstrap | dsrboot() |
— | R-only |
Core functionality is available in both languages: ALM, stepwise,
CALM, distributions, measures, rolling_origin, association
(pcor/mcor/determination), diagnostics (outlier_dummy),
manipulations (xreg_*, temporal_dummy), and EDA (stick). See the
parity matrix on Home.
See Resources for the full reference list.