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Results tagged with probability-or-statistics
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user 6358
Questions about systematic data collection and organization, or the application of probability theory to model the inherent patterns and properties of sampled data, underlying data distribution(s) or random processes.
3
votes
Expected value of a lognormal distribution
The function is Expectation not ExpectedValue. Unfortunately,
Expectation[b*x*(1 + ω*x^ρ)^κ, x \[Distributed] LogNormalDistribution[μ, σ]]
does not yield an answer.
If κ is an integer, it does ap …
- 20.4k
7
votes
Accepted
How to write down a probabilistic function in Wolfram Language?
For a one-off call:
RandomChoice[{0.25, 0.5, 0.25} -> {1, 2, 3}]
To make a function as you request:
f[d_] := RandomChoice[d[[All, 1]] -> d[[All, 2]]]
f[{{0.25, 1}, {0.5, 2}, {0.25, 3}}]
Note a c …
- 20.4k
1
vote
0
answers
60
views
Covariance of TimeSeries in v10.0-10.3
The following works in v11.2-12.0:
ts1 = TimeSeries[{{0, 0}, {1, 1}, {2, 0}, {3, 1}}];
ts2 = TimeSeries[{{0, 1}, {1, 0}, {2, 1}, {3, 0}}];
Covariance[ts1, ts2]
(* -1/3 *)
but fails in v10.0-10.3 wi …
- 20.4k
4
votes
3
answers
315
views
Expectation of a Sum
I'm using Expectation to calculate the Gaussian integral of a user-supplied function. The following works well and fast (< 1 second):
a[xi_, xj_] := E^(-1/2*(xi - xj)^2/σa^2);
Expectation[a[x[i], x[ …
- 20.4k
2
votes
Accepted
Polynomial fitting to obtain the growth rate
First, plot your data ($n$ vs $t$) on a log scale:
ListLogPlot[data]
As Roman suggests, a linear fit on log scale is the growth rate you're interested in. It doesn't look like there's any lag phase …
- 20.4k
7
votes
Sisyphus Random Walk
Another approach would be to formulate this as a DiscreteMarkovProcess. Since DiscreteMarkovProcess only allows a finite state space, we need to truncate at some large distance xmax. Also note that …
- 20.4k