Estimating the distribution of lag in the effect of short-term exposures and interventions: adaptation of a non-parametric regression spline model

2003 ◽  
Vol 22 (14) ◽  
pp. 2335-2363 ◽  
Author(s):  
B. Rachet ◽  
M. Abrahamowicz ◽  
A. J. Sasco ◽  
J. Siemiatycki
Keyword(s):  
Short Term ◽  
Parametric Regression ◽  
Regression Spline ◽  
Non Parametric

scholarly journals Inflation Rate Modelling in Indonesia

ETIKONOMI ◽  
2016 ◽  
Vol 15 (2) ◽  
pp. 111-124 ◽  
Author(s):  
Rezzy Eko Caraka ◽  
Wawan Sugiyarto
Keyword(s):  
Inflation Rate ◽  
Coefficient Of Determination ◽  
Money Stock ◽  
Parametric Regression ◽  
Regression Spline ◽  
Goods And Services ◽  
Crude Oil Prices ◽  
The Stability ◽  
The Relationship ◽  
Non Parametric

The purposes of this research were to analyse: (i) Modelling the inflation rate in Indonesia with parametric regression. (ii) Modelling the inflation rate in Indonesia using non-parametric regression spline multivariable (iii) Determining the best model the inflation rate in Indonesia (iv) Explaining the relationship inflation model parametric and non-parametric regression spline multivariable. Based on the analysis using the two methods mentioned the coefficient of determination (R2) in parametric regression of 65.1% while non-parametric amounted to 99.39%. To begin with, the factor of money supply or money stock, crude oil prices and the rupiah exchange rate against the dollar is significant on the rate of inflation. The stability of inflation is essential to support sustainable economic development and improve people's welfare. In conclusion, unstable inflation will complicate business planning business activities, both in production and investment activities as well as in the pricing of goods and services produced.DOI: 10.15408/etk.v15i2.3260

KEBANGGAAN TERHADAP BATIK MADURA BAGI WARGA SUMENEP

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Sayyida Sayyida ◽  
Nurdody Zakki
Keyword(s):  
Logistic Regression ◽  
Rural Areas ◽  
Research Method ◽  
Community Group ◽  
Parametric Regression ◽  
Logit Function ◽  
The Village ◽  
The City ◽  
Level Of Risk ◽  
Non Parametric

Diversity of Indonesian Batik hanging area. One of the very well-known Indonesian batik is Batik Madura. Batik Madura has become a pride for Indonesia, especially for Madura. The purpose of the study is to model the Sumenep pride to Batik Madura and to see the level of risk or tendency of batik madura pride for the community group Sumenep. This research method uses a non parametric regression used a non-parametric regression because the dependent variable in this study is the variable Y are variables not normally distributed. The results of this study states that the level of risk of the village in Sumenep proud of batik is almost 5 times higher than the islands while people in this city who live in the district town at risk Sumenep proud of Batik Madura 8-fold compared to the archipelago. So it can be concluded that the city is much more proud of batik than those who reside in rural areas especially those who reside in the islands. This study uses data from 100 questionnaires were analyzed using logistic regression analysis. The conclusion of this study is the pride of the batik model as follows: Function logistic regression / logit function: g (x) = 0,074 + 1,568X4(1)+2,159X4(2 this is case the islands as a comparison, X4(1)  is the place to stay in the village and X4(2)  is the place to stay in town, so the Model Opportunities p(x) = EXP(g(x))/1+EXP(g(x)).  Hopes for further research is to conduct research on the development of batik in an integrated region, the need to be disseminated to potential areas of particular potential in Madura batik, especially for residents who reside in the Islands.Keywords: Pride, Batik, Sumenep.

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