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Conditioned[expr,cond]

或 exprcond，表示以断言 cond 作为制约条件的 expr.

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Details and Options Details and Options
范例  
基本范例  
范围  
属性和关系  
参见
相关指南
历史
按以下格式引用：

Conditioned

Conditioned[expr,cond]

或 exprcond，表示以断言 cond 作为制约条件的 expr.

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范例

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基本范例  (2)

计算一个条件事件的概率：

Wolfram Language code: Probability[x ^ 2 > 12x > 2, xPoissonDistribution[2]]
Wolfram Language code: N[%]

用 NProbability 直接得到数字值：

Wolfram Language code: NProbability[x ^ 2 > 12x > 2, xPoissonDistribution[2]]

计算条件期望：

Wolfram Language code: Expectation[x ^ 5x > 2, xNormalDistribution[]]
Wolfram Language code: N[%]

用 NExpectation 直接得到数字值：

Wolfram Language code: NExpectation[x ^ 5x > 2, xNormalDistribution[]]

范围  (3)

计算一个离散分布的条件期望：

Wolfram Language code: Expectation[x ^ 2 + 3xx > 1, xPoissonDistribution[μ]]

连续分布：

Wolfram Language code: Expectation[x ^ 2 + 3xx > 1, xExponentialDistribution[3]]

导出分布：

Wolfram Language code: Expectation[x ^ 2 + 5x > 1, xTransformedDistribution[x ^ 3, xExponentialDistribution[2]]]

数据分布：

Wolfram Language code: data = RandomVariate[NormalDistribution[], 10^4];
Wolfram Language code: 𝒟 = HistogramDistribution[data];
Wolfram Language code: Expectation[x ^ 2x > 2, x𝒟]

多变量分布：

Wolfram Language code: Expectation[x ^ 2 + y(x + y > 1), {x, y}UniformDistribution[{{-1, 1}, {-2, 2}}]]

使用隐式时间来计算一个随机过程的条件概率：

Wolfram Language code: NProbability[x[1] > 7x[1] > 1, xPoissonProcess[4]]

使用相应的切片分布得到相同的结果：

Wolfram Language code: NProbability[x > 7x > 1, xPoissonProcess[4][1]]

使用隐式时间，随机过程的多变量切片的条件概率：

Wolfram Language code: Probability[x[5] > 1x[3] == 1 / 5, xWienerProcess[1 / 5, 2]]

使用相应的多变量切片分布得到相同的结果：

Wolfram Language code: Probability[y > 1x == 1 / 5, {x, y}WienerProcess[1 / 5, 2][{3, 5}]]

属性和关系  (4)

条件概率是两个概率的比值：

Wolfram Language code: expr1 = x ^ 2 < 30;expr2 = x > 1;
Wolfram Language code: Probability[expr1expr2, xPoissonDistribution[2]]
Wolfram Language code: Probability[expr1 && expr2, xPoissonDistribution[2]] / Probability[expr2, xPoissonDistribution[2]]

如果事件是互斥的，那么条件概率为0：

Wolfram Language code: expr1 = 3 < x < 5;expr2 = x > 7;
Wolfram Language code: Probability[expr1expr2, xPoissonDistribution[2]]
Wolfram Language code: Probability[expr2expr1, xPoissonDistribution[2]]

计算 TruncatedDistribution 中一个事件的概率：

Wolfram Language code: Probability[x ^ 2 > 1, xTruncatedDistribution[{-2, 3}, NormalDistribution[]]]
Wolfram Language code: N[%]

使用条件概率计算，得到相同的结果：

Wolfram Language code: Probability[x ^ 2 > 1 -2 < x < 3, xNormalDistribution[]]
Wolfram Language code: N[%]

对于独立变量，条件概率与无条件概率相同：

Wolfram Language code: 𝒟 = UniformDistribution[{{-3, 4}, {2, 5}}];
Wolfram Language code: Probability[x > 3y > 1, {x, y}𝒟]
Wolfram Language code: Probability[x > 3, {x, y}𝒟]
Wolfram Research (2010)，Conditioned，Wolfram 语言函数，https://reference.wolfram.com/language/ref/Conditioned.html.

文本

Wolfram Research (2010)，Conditioned，Wolfram 语言函数，https://reference.wolfram.com/language/ref/Conditioned.html.

CMS

Wolfram 语言. 2010. "Conditioned." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/Conditioned.html.

APA

Wolfram 语言. (2010). Conditioned. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/Conditioned.html 年

BibTeX

@misc{reference.wolfram_2026_conditioned, author="Wolfram Research", title="{Conditioned}", year="2010", howpublished="\url{https://reference.wolfram.com/language/ref/Conditioned.html}", note=[Accessed: 16-September-2026]}

BibLaTeX

@online{reference.wolfram_2026_conditioned, organization={Wolfram Research}, title={Conditioned}, year={2010}, url={https://reference.wolfram.com/language/ref/Conditioned.html}, note=[Accessed: 16-September-2026]}