$$ % Define your custom commands here \newcommand{\bmat}[1]{\begin{bmatrix}#1\end{bmatrix}} \newcommand{\E}{\mathbb{E}} \newcommand{\P}{\mathbb{P}} \newcommand{\S}{\mathbb{S}} \newcommand{\R}{\mathbb{R}} \newcommand{\S}{\mathbb{S}} \newcommand{\norm}[2]{\|{#1}\|_{{}_{#2}}} \newcommand{\pd}[2]{\frac{\partial #1}{\partial #2}} \newcommand{\pdd}[2]{\frac{\partial^2 #1}{\partial #2^2}} \newcommand{\vectornorm}[1]{\left|\left|#1\right|\right|} \newcommand{\abs}[1]{\left|{#1}\right|} \newcommand{\mbf}[1]{\mathbf{#1}} \newcommand{\mc}[1]{\mathcal{#1}} \newcommand{\bm}[1]{\boldsymbol{#1}} \newcommand{\nicefrac}[2]{{}^{#1}\!/_{\!#2}} \newcommand{\argmin}{\operatorname*{arg\,min}} \newcommand{\argmax}{\operatorname*{arg\,max}} \newcommand{\dd}{\operatorname{d}\!} $$

Latest figures

Every figure the wdm package draws for the real record, regenerated with the data.

Every figure wdm plots draws for the current diet, from the real record as of October 28, 2026. They are regenerated, with the presentation’s numbers, by one script whenever new days are logged, so nothing here is drawn by hand. The documentation explains how to read each one.

Weight and body composition

Raw weigh-ins (gray), the smoothed trend, and its 95% band. The trend is what moved; the scatter around it is mostly water.

Estimated fat and lean mass with their bands. Fat mass is weakly identified from a scale, so read its trend rather than its level.

The plan

Today’s plan: prescribed intake by week (top), and the predicted scale weight and tissue mass (bottom). Only the first day is eaten; tomorrow it is replanned.

Each day’s prescription, from the plans log, against what was eaten.

What the model has learned

What the filter believed about each metabolic parameter, day by day, relative to its prior (dashed line), with a 90% band. A band as wide as it started has learned nothing.

Where each parameter ended up, relative to its prior.

The maintenance estimate as it evolved (90% band), against the logged intake.

Diagnostics and inputs

Standardized one-step-ahead innovations: an honest model’s are centered on zero with a standard deviation near one and no pattern.

The raw log as entered: energy and exercise, macronutrients, fiber, sodium, and steps.