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Flexibility of ratetables predictors #2

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lrnv opened this issue Apr 4, 2024 · 5 comments
Closed

Flexibility of ratetables predictors #2

lrnv opened this issue Apr 4, 2024 · 5 comments

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@lrnv
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lrnv commented Apr 4, 2024

Supposons qu'a cet endroit il y a plusieurs covariablesd ans la table de mortalité (pas uniquement age, sex, year)

g = term(1) ~ foldl(+,term.(keys(rt.axes)))
g = apply_schema(g,schema(df))
pred_g = modelcols(g.rhs, df)

Alors juste en dessous on passer pred_g[:,1],pred_g[:,2] et pred_g[:,3], et on oublie d'éventuels pred_g[:,4]... Enfait il faudrait passer tout pred_g directement à la PoharPerme, a la place de age/year/sex uniquement. Mais ensuite la

function _Λ(T, Δ, age, year, sex, ratetable, grid)

il faudrait prendre en compte un pred_g complet... puis en tenir compte lors de l'appel aux tables de mortalité.

Je pense qu'il vaut mieux attendre que #1 soit mergé pour s'occuper de ça, ce sera plus simple avec les nouvelles tables de mortalités.

@rimhajal
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rimhajal commented Apr 4, 2024

Oui je vois maintenant ... On verra pour lundi alors

@rimhajal
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rimhajal commented Apr 4, 2024

It will be the same issue for the test

@lrnv
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lrnv commented Apr 4, 2024

Yes, same thing for the test.

@lrnv
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lrnv commented Apr 4, 2024

If you take a look at the comments i added in https://github.com/JuliaSurv/NetSurvival.jl/pull/1/files it points directly at the issue, but it will not be very hard to solve after #1 :)

Btw, if you have a fit function working for the test, it should be in this repository right ?

@lrnv lrnv changed the title Flexibilité des predicteurs de la table de mortalité Flexibility of ratetables predictors Apr 5, 2024
@lrnv
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lrnv commented May 2, 2024

So this should simply be closed.

@lrnv lrnv closed this as completed May 2, 2024
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