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Ditemukan 34823 dokumen yang sesuai dengan query
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Bohning, Dankmar
Boca Raton: CRC Press, Taylor & Francis Group, 2008
610.72 BOH m
Buku Teks SO  Universitas Indonesia Library
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Andrews, Frank M.
Michigan: University of Michigan, 1981
300.28 AND g
Buku Teks  Universitas Indonesia Library
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Boulder Colorado: Westview Press, 1980
362.1 ASS
Buku Teks  Universitas Indonesia Library
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Krieg, Eric J.
England: Pearson, 2014
519.5 KRI s;519.5 KRI s (2)
Buku Teks SO  Universitas Indonesia Library
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Blackman, Sheldon
New York: John Wiley & Sons, 1971
005.74 BLA i
Buku Teks SO  Universitas Indonesia Library
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Ismi Nadiya
"Suatu runtun waktu yang memiliki variabel respon biner disebut runtun waktu biner. Runtun waktu biner dapat dimodelkan menggunakan model umum Autoregressive dengan pendekatan regresi non-linier. Kedem Fokianos 2000 mengenalkan model runtun waktu biner melalui pendekatan Autoregressive dan regresi logistik. Metode yang digunakan untuk penaksiran parameter yaitu metode Partial Likelihood. Metode Partial Likelihood ini dilakukan dengan menentukan fungsi Partial Likelihood yang dibentuk dari probability density function pdf marginal distribusi Bernoulli. Namun, dalam proses penaksiran parameter menggunakan metode Partial Likelihood ditemukan kesulitan untuk mendapatkan solusi secara langsung dikarenakan persamaan yang tidak linier closed form. Oleh karena itu, untuk mengatasi hal tersebut dilakukan iterasi menggunakan metode Fisher Scoring.
Aplikasi data pada penaksiran parameter untuk model runtun waktu biner dalam tugas akhir ini menggunakan data kompetisi balap perahu antara Universitas Cambridge dan Universitas Oxford yang dicatat pada tahun 1946 sampai 2011 dengan jumlah data berbeda yaitu 22, 44, dan 66 data. Berdasarkan aplikasi data yang dilakukan, diperoleh hasil bahwa penaksiran parameter untuk model runtun waktu biner menggunakan Partial Likelihood dengan jumlah data yang berbeda menghasilkan penaksir parameter yang relatif sama atau tidak memiliki perbedaan yang signifikan.

A time series that has binary respon variable is called a binary time series. Binary time series can be modeled using the Autoregressive general model and nonlinear regression approach. Kedem Fokianos 2000 introduced a binary time series model through the Autoregressive and logistic regression approach. The parameters of binary time series are estimated using the Partial Likelihood method. The Partial Likelihood method is performed by determining the Partial Likelihood function derived from the marginal probability density function pdf of Bernoulli distribution. However, in the process of parameter estimation using this method, the form of final function to obtain parameters is not in the closed form equation. To face this problem, Fisher scoring iterations are perfomed.
The application of parameter estimation of the model uses the data about boat racing competition between the University of Cambridge and Oxford University from 1946 to 2011. Based on the data application, parameter estimation of the binary time series model using partial likelihood with different amounts of data resulting in a relatively same or no significant parameter estimator.
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Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2018
S-Pdf
UI - Skripsi Membership  Universitas Indonesia Library
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New York : John Wiley & Sons, 1970
004 DAT
Buku Teks SO  Universitas Indonesia Library
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Guetzkow, Harold
Englewood Cliffs, NJ: Prentice-Hall, 1972
300 GUE s
Buku Teks  Universitas Indonesia Library
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Xu zhang
"Abstrak
PURPOSE:
Chinese herbal medicine (CHM) has been widely used in China to treat allergic rhinitis (AR). However, several studies have produced conflicting data with regard to the efficacy of the medicine. Our aim was to perform a meta-analysis of randomized clinical trials (RCTs) to evaluate the relative efficacy of CHM.
METHODS:
We systematically searched the PubMed, Medline, and Springer electronic databases up to March 2017 for RCTs comparing the efficacy of CHM versus placebo for the treatment of patients with AR. Total nasal symptoms and quality of life were assessed through pooling mean difference (MD) with its 95% confidence interval (CI). Moreover, sensitivity and subgroup analyses according to control design and quality of life assessment were performed to evaluate the source of heterogeneity.
RESULTS:
Eleven RCTs were enrolled in the meta-analysis. Assessment of overall heterogeneity indicated significant heterogeneity among the individual studies (I²=100%, P<0.00001), and thus ransomed effects model was used to pool data. CHM was found to significantly enhance quality of life compared with placebo (MD=-0.88, (95% CI: -1.55, -0.21); P=0.01). The symptom of itchy nose, sneezing or total nasal symptoms scores were not significantly improved after CHM treatment, although the improvement in itchy nose just failed to reach significance (MD=0.09, (95% CI: 0.00, 0.18); P=0.06).
CONCLUSIONS:
This study suggests that CHM appears to improve the quality of life of AR patients. However, these findings, as well as the findings for the effect of CHM on sneezing, total nasal symptoms, and the symptom of itchy nose, need to be substantiated in larger cohorts of AR patients by further well-designed studies."
Suwon Korea: The Korean Academy of Asthma, Allergy and Clinical Immunology, 2018
610 AAIR 10:1 (2018)
Artikel Jurnal  Universitas Indonesia Library
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