Exercises8.1 Let X ~ and X = 0 be a random sample of X. Assume 0 follo terjemahan - Exercises8.1 Let X ~ and X = 0 be a random sample of X. Assume 0 follo Bahasa Indonesia Bagaimana mengatakan

Exercises8.1 Let X ~ and X = 0 be a

Exercises
8.1 Let X ~ and X = 0 be a random sample of X. Assume 0 follows a beta distribution with hyperparameters 0 and 0.
(a) Calculate the posterior mean of 0
(b) What is the conditional pf of 0 given the sample data x?
8.2 Let X ~ and 0~. Given the functions 0 and 0 for the 0 distribution in Table 8.2, identify the functions 0 and 0 as defined in equation (8.25) so that the 0 distribution is a natural conjugate of 0. Hence, derive the hyperparameters of the posterior distribution of 0 using equations (8.27) and (8.28).
8.3 In example 8.10, the mean squared error of the expected loss is analytically derived of the sample mean and the Buhlmann credibility estimate, and numerically estimated for the Bayes estimate. Derive the mean squared errors of the sample mean and the Buhlmann premium as predictors for future loss 0. Suggest a simulation procedure for the estimation of the mean squared error of the Bayes predictor for future loss.
8.4 Given 0. If the prior distribution of 0, determine the unconditional pf of X.
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Exercises8.1 Let X ~ and X = 0 be a random sample of X. Assume 0 follows a beta distribution with hyperparameters 0 and 0.(a) Calculate the posterior mean of 0(b) What is the conditional pf of 0 given the sample data x?8.2 Let X ~ and 0~. Given the functions 0 and 0 for the 0 distribution in Table 8.2, identify the functions 0 and 0 as defined in equation (8.25) so that the 0 distribution is a natural conjugate of 0. Hence, derive the hyperparameters of the posterior distribution of 0 using equations (8.27) and (8.28).8.3 In example 8.10, the mean squared error of the expected loss is analytically derived of the sample mean and the Buhlmann credibility estimate, and numerically estimated for the Bayes estimate. Derive the mean squared errors of the sample mean and the Buhlmann premium as predictors for future loss 0. Suggest a simulation procedure for the estimation of the mean squared error of the Bayes predictor for future loss.8.4 Given 0. If the prior distribution of 0, determine the unconditional pf of X.
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Latihan
8.1 Misalkan X ~ dan X = 0 menjadi sampel acak X. Asumsikan 0 mengikuti distribusi beta dengan hyperparameters 0 dan 0.
(a) Hitung mean posterior dari 0
(b) Apa pf bersyarat 0 diberikan sampel Data x?
8.2 Let X ~ dan 0 ~. Mengingat fungsi 0 dan 0 untuk 0 distribusi pada Tabel 8.2, mengidentifikasi fungsi 0 dan 0 sebagaimana didefinisikan dalam persamaan (8.25) sehingga 0 distribusi adalah konjugat alami 0. Oleh karena itu, memperoleh hyperparameters distribusi posterior 0 menggunakan persamaan (8.27) dan (8.28).
8.3 Dalam contoh 8.10, mean kuadrat kesalahan estimasi kerugian analitis berasal dari mean sampel dan Buhlmann kredibilitas estimasi, dan numerik estimasi perkiraan Bayes. Turunkan mean kuadrat kesalahan mean sampel dan premium Buhlmann sebagai prediktor kerugian di masa depan 0. Sarankan prosedur simulasi untuk estimasi mean kuadrat kesalahan prediktor Bayes kerugian di masa mendatang.
8.4 Mengingat 0. Jika distribusi sebelum 0 , menentukan pf tanpa syarat X.
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