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comment How to clear everything in Mathematica?
They may be looking for Remove
Aug
2
comment Clean & efficient bounding box non-intersection test
@BenP1192 you should post that as an answer. I found that you can include the bounding box in RegionIntersection, RegionIntersection[Line[ab], Line[cd], Rectangle[]]
Jul
30
comment How to define a bivariate skew normal distribution?
The Plot3D example doesn't work because the probability distribution needs to be pre-evaluated. Try adding an Evaluate in your code for SN. As for the random variates, you are still probably going to have to create your own method.
Jul
30
comment How to define a bivariate skew normal distribution?
Univariate is generally easy because one can use the inverse cdf if all else fails. Multivariate will probably never be implemented in full generality. Also, pretty much everything exists in closed form for multivariate normals so special case code exists for those.
Jul
30
comment How to define a bivariate skew normal distribution?
Sampling from user defined multivariate distributions isn't implemented. You will need to somehow use built in distributions or define your own method for sampling.
Jul
29
comment List all “duplicate” elements in Tally
@Mr.Wizard infix is a lovely obfuscator. If only there were short aliases for built in symbols for the purpose of code golf. Accessed via On["Golf"]. Though <<Golf' is probably better.
Jul
29
comment List all “duplicate” elements in Tally
@Mr.Wizard I'm one as well but clearly my kung fu is not as strong as yours :)
Jul
29
comment List all “duplicate” elements in Tally
Possibly GatherBy is what you need but without more specifics I can't say for sure.
Jul
28
comment Gauss Fit to List of 2D Points
@Rahul they make different assumptions about what the data represent. In your case we assume that the data points are left endpoints on the bins of a histogram (a perfectly reasonable assumption in this case). In the case of least squares there is a presumption that the data contain noise.
Jul
24
comment How should I iteratively refine a MixtureDistribution?
Part of the trouble I have is understanding what you mean by "configurations". If you could give an illustrative example of what you are attempting that would probably help. Data never hurts and short, clean, code always helps.
Jul
24
comment How should I iteratively refine a MixtureDistribution?
I think you will need to give some data driven example to give us a better idea how to help you.
Jul
23
comment Documentation for the Bounded option of SmoothKernelDistribution
It has been a long time since I saw the code but if memory serves it works by reflecting about the boundaries and truncating. The bandwidth is unaffected.
Jul
18
comment How to change the x-axis ticks from numbers to months
Take look at DateListPlot and TimeSeries
Jul
14
comment Fitting and plotting Weibull distribution
@SjoerdC.deVries I've unintentionally made things too complicated by trying to point out that the zeros get ignored. I was hoping to not get into any more detail than that :) Removing all reference to NonlinearModelFit
Jul
7
comment How to enter piecewise functions into Mathematica
I agree with you suggestions but think it is worth pointing out that Piecewise short circuits. So sometimes it is beneficial to sort the arguments such that the most common cases come first.
Jul
5
comment How I can count multiplications in an experssion?
@m_goldberg given the edit I believe this works now though I disagree with the accept.
Jul
5
comment How I can count multiplications in an experssion?
Very much cleaner than mine +1
Jul
1
comment How to create a thick spiral then extract the coordinates from the image?
This caused me to experiment with drawing random spiral galaxies. Thanks for the diversion!
Jun
21
comment Efficient Sampling of A (Countable) Discrete Distribution
Unfortunately 100k terms doesn't even reach the 99th percentile which is where things really slow down. Heavy tails are a pain.
Jun
21
comment Efficient Sampling of A (Countable) Discrete Distribution
You can get a small speed up by premultiplying by A and removing that from the test in the loop. A significant speed up can be gained by compilation. However, the given distribution has a very heavy tail and so it is tricky to be fast for large quantiles without some adaptive sampling which is also tricky since the distribution involves Zeta functions that can't be compiled.