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| [CourserHub.com].url |
123B |
| 01__mixturemodels.pdf |
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| 01__resources.html |
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| 01_acknowledgments-and-reference_instructions.html |
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| 01_aic-and-bic-in-selecting-the-order-of-ar-process.en.srt |
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| 01_aic-and-bic-in-selecting-the-order-of-ar-process.en.txt |
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| 01_aic-and-bic-in-selecting-the-order-of-ar-process.mp4 |
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| 01_algorithm.en.srt |
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| 01_background-for-lesson-1_instructions.html |
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| 01_background-for-lesson-1_L1_background.pdf |
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| 01_background-for-lesson-12_instructions.html |
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| 01_background-for-lesson-12_L12_background.pdf |
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| 01_background-for-lesson-4_instructions.html |
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| 01_background-for-lesson-4_L4_background.pdf |
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| 01_background-for-lesson-5_instructions.html |
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| 01_background-for-lesson-5_L5_background.pdf |
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| 01_basic-definitions.en.srt |
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| 01 bayesian-inference-in-the-ar-p-reference-prior-conditional-likelihood en srt |
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| 01_components-of-bayesian-models.en.srt |
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| 01_introduction-to-linear-regression.en.srt |
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| 01_introduction-to-logistic-regression.en.srt |
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| 01_lesson-6-1-priors-and-prior-predictive-distributions.mp4 |
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| 01_lesson-7-1-bernoulli-binomial-likelihood-with-uniform-prior.en.txt |
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| 01_lesson-8-1-poisson-data.en.srt |
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| 01_markov-chain-monte-carlo-algorithms-part-1.mp4 |
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| 01_markov-chains_background_MarkovChains.html |
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| 01_markov-chains_instructions.html |
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| 01_mixture-model-introduction-data-and-code_instructions.html |
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| 01_mixture-model-introduction-data-and-code_lesson_11mixture.html |
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| 01_mixture-model-introduction-data-and-code_mixture.csv |
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| 01_mixture-models-and-naive-bayes-classifiers.en.srt |
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| 01_mixture-models-for-clustering.en.srt |
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| 01_mixture-models-for-clustering.mp4 |
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| 01_module-2-assignments-and-materials_instructions.html |
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| 01 module-2-objectives-assignments-and-supplementary-materials instructions html |
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| 01_module-3-assignments-and-materials_instructions.html |
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| 01_module-4-assignments-and-materials_instructions.html |
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| 01 module-4-objectives-assignments-and-supplementary-materials instructions html |
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| 01_monte-carlo-integration.en.srt |
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| 01_monte-carlo-integration.en.txt |
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| 01_monte-carlo-integration.mp4 |
37.91MB |
| 01_multiple-factor-anova_instructions.html |
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| 01_multiple-factor-anova_lesson_08multipleANOVA.html |
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| 01_multiple-parameter-sampling-and-full-conditional-distributions.en.srt |
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| 01_multiple-parameter-sampling-and-full-conditional-distributions.mp4 |
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| 01_ndlm-definition.en.srt |
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| 01_numerical-stability.en.srt |
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| 01_prediction-for-location-mixture-of-ar-models.en.srt |
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| 01_prediction-for-location-mixture-of-ar-models.mp4 |
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| 01 review-of-maximum-likelihood-and-bayesian-inference-in-regression Bayesian regression review pdf |
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| 01 review-of-maximum-likelihood-and-bayesian-inference-in-regression instructions html |
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| 01_stationarity.en.srt |
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| 01_stationarity.mp4 |
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| 01_the-ar-1.en.srt |
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| 01_trace-plots-autocorrelation.en.srt |
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| 01_trace-plots-autocorrelation.mp4 |
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| 01_welcome-to-bayesian-statistics-mixture-models.en.srt |
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| 01_welcome-to-bayesian-statistics-mixture-models.mp4 |
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| 01_welcome-to-bayesian-statistics-time-series.en.srt |
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| 01_welcome-to-bayesian-statistics-time-series.mp4 |
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| 02_aic-and-bic-example_instructions.html |
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| 02_an-introduction-to-r_instructions.html |
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| 02_density-estimation-example.mp4 |
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| 02_further-reading-and-acknowledgements_furtherReading_refs.pdf |
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| 07_introduction-to-r.en.srt |
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| 07_introduction-to-r.en.txt |
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| 07_introduction-to-r.mp4 |
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| 07_linear-regression-example-in-jags.en.srt |
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| 07_linear-regression-example-in-jags.en.txt |
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| 07_linear-regression-example-in-jags.mp4 |
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| 07_location-and-scale-mixture-of-ar-model_instructions.html |
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| 07_mcmc-example-2.en.srt |
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| 07_mcmc-example-2.en.txt |
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| 07_mcmc-example-2.mp4 |
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| 07_r-code-simulate-data-from-a-white-noise-process_instructions.html |
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| 07 sample-code-for-estimating-the-number-of-components-and-the-partition-structure instructions html |
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| 07_smoothing-in-the-ndlm-example.en.srt |
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| 07_smoothing-in-the-ndlm-example.en.txt |
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| 07_smoothing-in-the-ndlm-example.mp4 |
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| 07_spectral-representation-of-the-ar-p.en.srt |
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| 07_spectral-representation-of-the-ar-p.en.txt |
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| 07_spectral-representation-of-the-ar-p.mp4 |
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| 07_the-ar-p-review_instructions.html |
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| 07_the-ar-p-review_summary.pdf |
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| 08_applications-of-hierarchical-modeling_hierarchicalModelApplications.pdf |
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| 08_applications-of-hierarchical-modeling_instructions.html |
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| 08_example-of-a-zero-inflated-log-gaussian-distribution_instructions.html |
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| 08_plotting-the-likelihood-in-r.en.srt |
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| 08_plotting-the-likelihood-in-r.en.txt |
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| 08_plotting-the-likelihood-in-r.mp4 |
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| 08_prediction-for-ar-models.en.srt |
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| 08_prediction-for-ar-models.mp4 |
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| 08_rcode-smoothing-in-the-ndlm-example_instructions.html |
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| 08_sample-code-for-mcmc-example-2_instructions.html |
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| 08_spectral-representation-of-the-ar-p-example.en.srt |
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| 08_spectral-representation-of-the-ar-p-example.en.txt |
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| 08_spectral-representation-of-the-ar-p-example.mp4 |
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| 09_ar-model-prediction-example_instructions.html |
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| 09_code-and-data-for-lesson-11_cookies.dat |
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| 09_code-and-data-for-lesson-11_instructions.html |
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| 09_code-and-data-for-lesson-11_lesson_11.html |
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| 09_plotting-the-likelihood-in-excel.en.srt |
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| 09_plotting-the-likelihood-in-excel.en.txt |
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| 09_plotting-the-likelihood-in-excel.mp4 |
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| 09_rcode-spectral-density-of-ar-p_instructions.html |
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| 09_second-order-polynomial-filtering-and-smoothing-example.en.srt |
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| 09_second-order-polynomial-filtering-and-smoothing-example.en.txt |
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| 09_second-order-polynomial-filtering-and-smoothing-example.mp4 |
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| 10_arima-processes_ARIMA.pdf |
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| 10_arima-processes_instructions.html |
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| 10_extended-ar-model_Honor-Extend_AR_model.pdf |
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| 10_extended-ar-model_instructions.html |
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| 10_using-the-dlm-package-in-r.en.srt |
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| 10_using-the-dlm-package-in-r.en.txt |
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| 11_rcode-using-the-dlm-package-in-r_instructions.html |
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| Readme.txt |
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