{"type":"standard","title":"Exponentially modified Gaussian distribution","displaytitle":"Exponentially modified Gaussian distribution","namespace":{"id":0,"text":""},"wikibase_item":"Q5421535","titles":{"canonical":"Exponentially_modified_Gaussian_distribution","normalized":"Exponentially modified Gaussian distribution","display":"Exponentially modified Gaussian distribution"},"pageid":34299105,"thumbnail":{"source":"https://upload.wikimedia.org/wikipedia/commons/thumb/1/1c/EMG_Distribution_PDF.png/330px-EMG_Distribution_PDF.png","width":320,"height":320},"originalimage":{"source":"https://upload.wikimedia.org/wikipedia/commons/1/1c/EMG_Distribution_PDF.png","width":480,"height":480},"lang":"en","dir":"ltr","revision":"1283981272","tid":"d7670905-1199-11f0-a054-e78cacd7f10f","timestamp":"2025-04-04T21:14:49Z","description":"Describes the sum of independent normal and exponential random variables","description_source":"local","content_urls":{"desktop":{"page":"https://en.wikipedia.org/wiki/Exponentially_modified_Gaussian_distribution","revisions":"https://en.wikipedia.org/wiki/Exponentially_modified_Gaussian_distribution?action=history","edit":"https://en.wikipedia.org/wiki/Exponentially_modified_Gaussian_distribution?action=edit","talk":"https://en.wikipedia.org/wiki/Talk:Exponentially_modified_Gaussian_distribution"},"mobile":{"page":"https://en.m.wikipedia.org/wiki/Exponentially_modified_Gaussian_distribution","revisions":"https://en.m.wikipedia.org/wiki/Special:History/Exponentially_modified_Gaussian_distribution","edit":"https://en.m.wikipedia.org/wiki/Exponentially_modified_Gaussian_distribution?action=edit","talk":"https://en.m.wikipedia.org/wiki/Talk:Exponentially_modified_Gaussian_distribution"}},"extract":"In probability theory, an exponentially modified Gaussian distribution describes the sum of independent normal and exponential random variables. An exGaussian random variable Z may be expressed as Z = X + Y, where X and Y are independent, X is Gaussian with mean μ and variance σ2, and Y is exponential of rate λ. It has a characteristic positive skew from the exponential component.","extract_html":"
In probability theory, an exponentially modified Gaussian distribution describes the sum of independent normal and exponential random variables. An exGaussian random variable Z may be expressed as Z = X + Y, where X and Y are independent, X is Gaussian with mean μ and variance σ2, and Y is exponential of rate λ. It has a characteristic positive skew from the exponential component.
"}{"fact":"Cats only use their meows to talk to humans, not each other. The only time they meow to communicate with other felines is when they are kittens to signal to their mother.","length":170}
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