Glossary

Purpose

Define canonical terms used across DSAMbayes modelling, runner, diagnostics, and release documentation.

How to use this glossary

  1. Use these definitions when writing or reviewing DSAMbayes documentation.
  2. Keep term usage consistent across docs/modelling/, docs/runner/, and docs/internal/.
  3. If a term changes behaviour in code, update this page in the same change.

Terms

Term Definition Primary location
adstock Media carry-over transform that spreads spend effect over subsequent periods. Stan media-transform templates and modelling docs
allocation Post-fit budget optimisation stage (allocation.* in YAML). docs/runner/config-schema.md
artefact File written by runner validate/run workflows. docs/runner/output-artifacts.md
baseline term Non-media explanatory term (for example trend, seasonality, holiday controls). docs/modelling/diagnostics-gates.md
blm Base DSAMbayes model class for non-pooled regression workflows. R/blm.R
blocked CV Expanding-window time-series cross-validation used for model selection. R/time_series_cv.R
boundary Lower and upper constraints on model parameters. docs/modelling/priors-and-boundaries.md
chain diagnostics MCMC quality diagnostics such as Rhat, ESS, and divergence indicators. R/diagnostics.R
config resolution Process of applying defaults, coercions, path normalisation, and validation to YAML. R/run_config_*.R
CRE Correlated random effects approach using Mundlak-style within and between variation terms. R/cre_mundlak.R
decomp Post-fit decomposition of fitted response into predictor-level contributions. R/decomp.R
diagnostics gate Thresholded pass/warn/fail policy checks over model diagnostics. R/diagnostics_report.R
divergence Stan sampler warning indicating problematic Hamiltonian trajectories. MCMC diagnostics outputs
dry run Runner mode that validates config and data without Stan fitting (validate). scripts/dsambayes.R
ELPD Expected log predictive density, used for predictive model comparison. R/compare_runs.R
ESS Effective sample size for MCMC draws. Higher is generally better. Chain diagnostics outputs
fit MCMC fitting path (fit.method: mcmc). R/run_from_yaml.R
fit_map / optimise MAP optimisation path (fit.method: optimise). R/blm.R, R/hierarchy.R, R/pooled.R
hierarchical Model class with grouped random effects (`(term group)` syntax).
identifiability check Diagnostic check for baseline and media term correlation risk. R/diagnostics_report.R
kpi scale Business-outcome scale used for reporting. For log-response models this is back-transformed from model scale. docs/modelling/response-scale-semantics.md
lognormal_ms Positive-support prior family parameterised by mean and standard deviation on the original scale. R/prior_schema.R
MAP Maximum a posteriori point estimate from optimisation. Not a posterior mean. fit_map paths
MCMC Markov chain Monte Carlo posterior sampling. rstan::sampling paths
Pareto-k PSIS-LOO reliability diagnostic for influence of observations. loo_summary.csv outputs
pooled Model class with structured pooling over configured grouping variables. R/pooled.R
posterior draw One sampled value from the posterior distribution. get_posterior() outputs
pre-flight checks Guardrails and model/data compatibility checks run before fitting. R/pre_flight.R
prior_only Fit mode sampling only from priors, excluding likelihood learning. prep_data_for_fit.* interfaces
PSIS-LOO Pareto-smoothed importance-sampling leave-one-out approximation. R/diagnostics_report.R
QG-1 to QG-7 Canonical release quality gates for lint, style, tests, package check, runner smoke, and docs build. docs/internal/quality-gates.md
response scale Scale used inside the fitted model (identity or log). docs/modelling/response-scale-semantics.md
Rhat Convergence diagnostic comparing within- and between-chain variance. Chain diagnostics outputs
runner YAML/CLI execution layer around core DSAMbayes APIs. scripts/dsambayes.R, R/run_from_yaml.R
run_dir Output directory used by a runner validate/run execution. docs/runner/output-artifacts.md
staged layout Structured artefact layout with numbered folders (00_ to 70_). docs/runner/output-artifacts.md
Stan cache Compiled model cache location, typically under XDG_CACHE_HOME. install/setup docs
SMAPE Symmetric mean absolute percentage error metric used in fit summaries. R/stats.R
time-components Managed time control features, including holiday-derived regressors. R/holiday_calendar.R
tscv Time-series selection artefact prefix for blocked CV outputs. 50_model_selection/tscv_*.csv
warmup Initial MCMC iterations used for adaptation and excluded from posterior draws. fit.mcmc.warmup
Hill transform Saturation function spend^n / (spend^n + k^n) used in budget optimisation response curves. k is the half-saturation point, n is the shape parameter. R/optimise_budget.R
atan transform Saturation function atan(spend / scale) mapping spend to a bounded response. R/optimise_budget.R
log1p transform Saturation function log(1 + spend / scale) providing diminishing-returns concavity. R/optimise_budget.R
adstock Media carry-over transform that spreads a spend effect over subsequent periods via geometric decay. Applied as a pre-transform in the data, not estimated within DSAMbayes. Formula transforms
conditional mean Bias-corrected back-transform for log-response models: exp(mu + sigma^2/2). Default in v1.2.2 for fitted_kpi(). R/fitted.R
Jensen's inequality Mathematical property that E[exp(X)] != exp(E[X]) when X has non-zero variance. DSAMbayes avoids this bias by applying exp() draw-wise before summarising. docs/modelling/response-scale-semantics.md