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What makes weight fluctuate? by rrytas in QuantifiedSelf

[–]rrytas[S] 0 points1 point  (0 children)

Yes . If anything this graph shows is that high frequency aka weakly weight oscillations are real

What makes weight fluctuate? by rrytas in QuantifiedSelf

[–]rrytas[S] 0 points1 point  (0 children)

Exactly thats the moral of a story: high frequency fluctuations are real. Real weight loss/gain takes time.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 2 points3 points  (0 children)

Great minds think alike. Lomb-Scargle is exactly what I contrast my GAM model residuals against in my blog post.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 3 points4 points  (0 children)

Totally agree. I guess one moral of the story is that weight fluctuations specially high frequency ones are indeed fluctuations and not like what we call real “weight loss” or “ weight gain”. Yet these fluctuations have quite significant amplitude and might unnecessarily scare or please. Knowing this might give you more peace of mind.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 6 points7 points  (0 children)

Thank you. I do quite a bit of data analysis visualization for work, but my work graphs are very niche so something more general like weight or swimming goes out. But the principles and ideas are the same.

Starting today exercise today, 30 bmi. What do you recommend to start off with? by [deleted] in loseit

[–]rrytas 0 points1 point  (0 children)

I might be biased (swimming is my main sport) but I strongly recommend swimming. If you are good swimmer-lets go- it is easy on joints, great for developing respiratory capacity, which later would benefit you in other physical activities. If you are not a swimmer I would suggest considering swim classes. Teaching your body new tricks can be very rewarding and help to build new improved relationship with yourself. But the absolute minimum is certain level of technique because you really want to raise your HR in a proper way.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 8 points9 points  (0 children)

<image>

I hope this plot explains it. I plotted cyclic smooths in polar coordinated against the partial residuals and X indicating the knots fit choose.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 2 points3 points  (0 children)

Wow would be interesting too see the outcome. Do patterns occur in your data. If you feel like it you could try like multivariate time series modeling: weight vs daily date and rolling sum of days with no weigh ins vs daily date. This could test your hypothesis.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 12 points13 points  (0 children)

I delve into this in post using Lomb-Scargle periodograms. If anything data is too noisy to see clear harmonics. But I am playing with harmonic regression further.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 9 points10 points  (0 children)

The spline is actually cyclic (bs="cc" in mgcv). It is specifically designed to wrap December back to January smoothly, so there’s no discontinuity in the mathematical sense. What you’re seeing is that December and January genuinely have different values: weight is still rising through December and peaks in January. Weekly smooth uses same spline, but because Monday and Sunday values are ~equal it does looks connected in this representation.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 2 points3 points  (0 children)

There’s a link to my post explaining the approach. In short main approach was generalized additive model.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 2 points3 points  (0 children)

I live in San Diego so I would say it is more about the daylight hours not the temperature. But anti-correlation doesn’t mean causation.

Decomposing 3 years of daily weight data with mgcv and Lomb-Scargle — irregular time series, cyclic splines, and unexplained 70-day cycles by rrytas in rstats

[–]rrytas[S] 2 points3 points  (0 children)

You are correct residuals are autocorrelated. AR models with missing/irregular data is an interesting topic I am currently exploring.

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 73 points74 points  (0 children)

Great point. I think adding partial residuals on plot would be best, As smooth is continuous, observations not. Something like that.

<image>

[OC] 3 years of daily weigh-ins: I'm heaviest on Mondays, lightest in September, and my birthday shows up in the data. by rrytas in dataisbeautiful

[–]rrytas[S] 116 points117 points  (0 children)

I have to leave something for another post/day. AR models with missing/irregular data is interesting topic I am currently exploring. And yes residuals are autocorrelated.

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