Skip to main content

probability or statistics - Why does conditional NExpectation fail for a multivariate distribution?


To give an example for a multiparametric distribution let us take a binormal distribution:


binormalDist = With[
{
μ = { 0, 0 },
σ = { 1, 1 },
ρ = 7/10

},
BinormalDistribution[ μ, σ, ρ ]
];

Calculating the conditional expectation in simple cases works out:


NExpectation[2 x + 3 \[Conditioned] x < 1., {x, y} \[Distributed] binormalDist ]


2.4248




and so does this too:


NExpectation[2 x + 3 \[Conditioned] y == 2., {x, y} \[Distributed] binormalDist ]


5.8



but


NExpectation[2 x + 3 \[Conditioned] (x < 1 && y == 2.), {x, y} \[Distributed] binormalDist ]

is returned unevaluated (as is Expectation with identical args)




NExpectation[ 3+ 2 x [Conditioned] x < 1 && y == 2., {x, y} [Distributed] BinormalDistribution[{0, 0}, {1, 1}, 7/10]]



Why? And how can it be solved?



Answer



Since


Probability[x < 1 && y == 2,
{x, y} \[Distributed] BinormalDistribution[{0, 0}, {1, 1}, 7/10]]
0


and the PDF of the purported conditional distribution has that expression as a denominator, this may be the reason why your attempt remains unevaluated.




Using Method -> "Trace", we see that NExpectation[] is attempting to evaluate the following expression internally:


NIntegrate[(3 + 2 x)
PDF[Statistics`Library`ConditionalDistribution[x < 1 && y == 2,
{x, y} \[Distributed] BinormalDistribution[{0, 0}, {1, 1}, 7/10]], {x, y}],
{x, -∞, ∞}, {y, -∞, ∞}, AccuracyGoal -> ∞, Compiled -> Automatic,
PrecisionGoal -> Automatic, WorkingPrecision -> MachinePrecision,
MinRecursion -> 1]


where we see that Statistics`Library`ConditionalDistribution[] is used to represent the distribution induced by the conditional expectation. Notice that both PDF[Statistics`Library`ConditionalDistribution[x < 1, {x, y} \[Distributed] BinormalDistribution[{0, 0}, {1, 1}, 7/10]], {x, y}] and PDF[Statistics`Library`ConditionalDistribution[y == 2, {x, y} \[Distributed] BinormalDistribution[{0, 0}, {1, 1}, 7/10]], {x, y}] evaluate to expressions, but PDF[Statistics`Library`ConditionalDistribution[x < 1 && y == 2, {x, y} \[Distributed] BinormalDistribution[{0, 0}, {1, 1}, 7/10]], {x, y}] does not.


If you think Mathematica should be able to evaluate combined conditions like in the OP, you could try writing a suggestion to support.


Comments

Popular posts from this blog

plotting - How to draw lines between specified dots on ListPlot?

I would like to create a plot where I have unconnected dots and some connected. So far, I have figured out how to draw the dots. My code is the following: ListPlot[{{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4,13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full] I have thought using ListLinePlot command, but I don't know how to specify to the command to draw only selected lines between the dots. Do have any suggestions/hints on how to do that? Thank you. Answer One possibility would be to use Epilog with Line : ListPlot[ {{1, 1}, {2, 2}, {3, 3}, {4, 4}, {1, 4}, {2, 5}, {3, 6}, {4, 7}, {1, 7}, {2, 8}, {3, 9}, {4, 10}, {1, 10}, {2, 11}, {3, 12}, {4, 13}, {2.5, 7}}, Ticks -> {{1, 2, 3, 4}, None}, AxesStyle -> Thin, TicksStyle -> Directive[Black, Bold, 12], Mesh -> Full, Epilog -> { Line[ ...

equation solving - Invert and fit implicitly defined curve

I need to fit an implicitly defined curve. I thought I could get some data out of Solve , and then using FindFit . Therefore, I would like to find the relation the parametric curve defined by $F(x,y)=0$: Solve[-(1/2) + 1/2 (0.41202 BesselK[0, 0.1 Sqrt[x^2 + y^2]] + (0.101483 x BesselK[1, 0.1 Sqrt[x^2 + y^2]])/Sqrt[x^2 + y^2]) == 0, y] But I can't get an output: Solve was unable to solve the system with inexact coefficients or the system obtained by direct rationalization of inexact numbers present in the system. Since many of the methods used by Solve require exact input, providing Solve with an exact version of the system may help. >> Edit: In particular, I would like to fit the data coming from the curve with the expression of another curve, and not with a function $f(x)$. In particular, since this clearly looks like a cardioid , I would like it to fit to something like it. What other strategies could I try?

dynamic - How can I make a clickable ArrayPlot that returns input?

I would like to create a dynamic ArrayPlot so that the rectangles, when clicked, provide the input. Can I use ArrayPlot for this? Or is there something else I should have to use? Answer ArrayPlot is much more than just a simple array like Grid : it represents a ranged 2D dataset, and its visualization can be finetuned by options like DataReversed and DataRange . These features make it quite complicated to reproduce the same layout and order with Grid . Here I offer AnnotatedArrayPlot which comes in handy when your dataset is more than just a flat 2D array. The dynamic interface allows highlighting individual cells and possibly interacting with them. AnnotatedArrayPlot works the same way as ArrayPlot and accepts the same options plus Enabled , HighlightCoordinates , HighlightStyle and HighlightElementFunction . data = {{Missing["HasSomeMoreData"], GrayLevel[ 1], {RGBColor[0, 1, 1], RGBColor[0, 0, 1], GrayLevel[1]}, RGBColor[0, 1, 0]}, {GrayLevel[0], GrayLevel...