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-as, -dj, -dp, -dt, and -dc have no effect in a daylight coefficient simulation with rcontrib, so you can ignore those.

The parameters you're using look similar the parameters I recommend for the interior view matrix of a three-phase calculation, which was determined with convergence testing on the BRE-IDMP dataset.For convergence testing I recommend taking roughly 1% of the test points and running simulations with varied parameters. The points chosen should be some of the more challenging, further from the window and in corners.

The critical parameters for matrix generation (with glow materials as light sources) are usually -ab, -ad, and -lw. I'd recommend something like this:

for ab in 6 8 10 12 ; do
for ad in 1024 4096 16384 65536 262142 ; do
for lw_power in 1 1.5 2 2.5 3 ; do
lw = 1 / (ad^lw_power)

rcontrib ... -ab $ab -ad $ad -lw $lw ...  < fewpoints.txt > result_${ab}_${ad}_${lw}.mtx

done; done; done

Then you can either compare the difference in matrix values, or you can generate a test set of sky vectors (sunny morning, sunny noon, sunny evening, overcast, etc.) and compare illuminance results between the runs. Then if thee's a big jump between ab 6 and 8, a small jump between 8 and 10, but only a minor difference between 10, and 12, you're okay with -ab 10. You could go back and test -ab 9 in a second run, if you want to be superbly optimal. If there's still a sizable jump between 10 and 12, then maybe run some more with -ab 14 and 16. I find it helpful to plot results, that way you can see if things flatten out, and you can also recognize noise (which will be apparent with low -ad and -lw runs)

You might also want to time the simulations, so you can estimate the full run length (which is semi-linear with number of simulation points).

And finally, rfluxmtx (which calls rcontrib in the background) has simplified the process of daylight coefficient simulations greatly. You might want to look at Sarith's tutorial and consider using rfluxmtx instead of rcontrib. https://www.radiance-online.org/learning/tutorials/matrix-based-methods