Strong Ordinal Properties of an Additive Model for the Sequential Processing of Probabilistic Information

A Bayesian model that provides probabilistic information about the spread of malignancy in a Hodgkin’s disease patient has been developed at the Tufts New England Medical Center. In assessing the model’s reliability, it seemed important to use it to make predictions about patients other than those relevant to its construction. The accuracy of these predictions could then be tested statistically. This paper describes such a test, based on 243 Hodgkin’s disease patients of known pathologic stage. The results obtained were supportive of the model, and the test procedure might interest those wishing to determine whether the imperfections that attend any attempt to make probabilistic forecasts have gravely damaged their accuracy.

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Perbandingan Linieritas Dalam Pendeteksian Faktor-Faktor Yang Mempengaruhi Angka Kematian Bayi Di Provinsi Aceh

Talenta Conference Series Science and Technology (ST) ◽

10.32734/st.v2i2.460 ◽

2019 ◽

Vol 2 (2) ◽

Author(s):

Desfira Ahya ◽

Inas Salsabila ◽

Miftahuddin

Keyword(s):

Mortality Rate ◽

Infant Mortality ◽

Linear Model ◽

Health Workers ◽

Additive Model ◽

Infant Mortality Rate ◽

Mortality Data ◽

Important Indicator ◽

Penalized Spline ◽

Aceh Province

Angka Kematian Bayi/ Infant Mortality Rate (IMR) merupakan indikator penting dalam mengukur keberhasilan pengembangan kesehatan. Nilai IMR juga dapat digunakan untuk mengetahui tingkat kesehatan ibu, kondisi kesehatan lingkungan dan secara umum, tingkat pengembangan sosio-ekonomi masyarakat. Penelitian ini bertujuan untuk memperoleh model IMR terbaik menggunakan tiga pendekatan: Model Linear, Model Linear Tergeneralisir dan Model Aditif Tergeneralisir dengan basis P-spline. Sebagai tambahan, berdasarkan model tersebut akan terlihat variabel yang mempengaruhi tingkat kematian bayi di provinsi Aceh. Penelitian ini menggunakan data jumlah kematian bayi di tahun 2013-2015. Data dalam penelitian ini diperoleh dari Profil Kesehatan Aceh. Hasil menunjukkan bahwa model terbaik dalam menjelaskan angka kematian bayi di provinsi Aceh tahun 2013-2015 ialah Model Linear Tergeneralisir dengan basis P-spline menggunakan parameter penghalusan 100 dan titik knots 8. Faktor yang sangat mempengaruhi angka kematian ialah jumlah pekerja yang sehat. Infant mortality rate (IMR) is an important indicator in measuring the success of health development. IMR also can be used to knowing the level of maternal health, environmental health conditions and generally the level of socio-economic development in community. This research aims to get the best model of infant mortality data using three approaches: Linear Model, Generalized Linear Model and Generalized Additive Model with Penalized Spline (P-spline) base. In addition, based on the model can be seen the variables that affect to infant mortality in Aceh Province. This research uses data number of infant mortality in Aceh Province period 2013-2015. The data in this research were obtained from Aceh’s Health Profile. The results show that the best model can be explain infant mortality rate in Aceh Province period 2013-2015 is GAM model with P-spline base using smoothing parameter 100 and knots 8. Factor that high effect to infant mortality is number of health workers.

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Applying generalized additive model to integrate digital elevation model and remotely sensed data to predict the vegetation distribution

Chinese Journal of Plant Ecology ◽

10.3724/sp.j.1258.2012.01106 ◽

2013 ◽

Vol 36 (10) ◽

pp. 1106-1119

Author(s):

Chuang-Ye SONG ◽

Hui-Ming LIU ◽

Gao-Huan LIU ◽

Chong HUANG

Keyword(s):

Digital Elevation Model ◽

Generalized Additive Model ◽

Additive Model ◽

Remotely Sensed ◽

Vegetation Distribution ◽

Remotely Sensed Data ◽

Digital Elevation ◽

Elevation Model

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Wages, BMI, and Age: A Generalized Additive Model Using the Oracle Estimator

SSRN Electronic Journal ◽

10.2139/ssrn.1975044 ◽

2011 ◽

Author(s):

Christian Gregory

Keyword(s):

Generalized Additive Model ◽

Additive Model

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Additive-multiplicative description of extrathermodynamic relations: Application to solvent effect

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19900634 ◽

1990 ◽

Vol 55 (3) ◽

pp. 634-643 ◽

Cited By ~ 2

Author(s):

Oldřich Pytela

Keyword(s):

Solvent Effect ◽

Additive Model ◽

Multiplicative Model ◽

Data Matrix ◽

Statistical Parameters ◽

Model Application ◽

Mutual Correlation ◽

Linear Free Energy ◽

Cross Terms ◽

Energy Relationships

The paper is focused on evaluation of significance of the additive-multiplicative model of extrathermodynamic relations (linear free energy relationships) as compared with the additive model. Application of the method of conjugated deviations to a data matrix describing manifestations of solvent effects in 367 processes in solutions (6 334 data) has shown that introduction of cross-terms into the additive model is statistically significant for a model with two and particularly three parameters. At the same time the calculation has provided a new set of statistical parameters for description of solvent effect with application of the additive-multiplicative model. Compared with an analogous set designated for the additive model, the new parameters show a lower mutual correlation, retaining the same nature of the properties described, i.e. polarity-acidity (PAC parameter), polarity-basicity (PBC), and polarity-polarizability (PPC).

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