#estimator — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #estimator, aggregated by home.social.
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'Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations', by Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao.
http://jmlr.org/papers/v25/22-1159.html
#estimation #estimator #odes -
`Intuitively, if the restricted #estimator is near the maximum of the #likelihood function, the score should not differ from zero by more than sampling error. While the finite sample #distributions of score tests are generally unknown, they have an #asymptotic χ2-distribution under the null #hypothesis as first proved by C. R. Rao in 1948, a fact that can be used to determine statistical #significance.`
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`Intuitively, if the restricted #estimator is near the maximum of the #likelihood function, the score should not differ from zero by more than sampling error. While the finite sample #distributions of score tests are generally unknown, they have an #asymptotic χ2-distribution under the null #hypothesis as first proved by C. R. Rao in 1948, a fact that can be used to determine statistical #significance.`
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`Intuitively, if the restricted #estimator is near the maximum of the #likelihood function, the score should not differ from zero by more than sampling error. While the finite sample #distributions of score tests are generally unknown, they have an #asymptotic χ2-distribution under the null #hypothesis as first proved by C. R. Rao in 1948, a fact that can be used to determine statistical #significance.`
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`Intuitively, if the restricted #estimator is near the maximum of the #likelihood function, the score should not differ from zero by more than sampling error. While the finite sample #distributions of score tests are generally unknown, they have an #asymptotic χ2-distribution under the null #hypothesis as first proved by C. R. Rao in 1948, a fact that can be used to determine statistical #significance.`