The aim of this research is to forecast the consumer price index (CPI) of education, recreation, and sport in Indonesia using feedforward neural network (FFNN) model. We consider two FFNN models which are differed from the inputs. The inputs of the first model are generated by considering the inputs such as in a time series model, those are the lags of the CPI. Regarding that the pattern of the...

Random regression models (RRM) have become common for the analysis of longitudinal data or repeated records on individual over time. The goal of this paper was to explore the use of random regression models with orthogonal / Legendre polynomials (RRL) to analyze new repeated measures called clutch size (CS) as a meristic trait for Iranian native fowl. Legendre polynomial functions of increasing...

In this article we investigate the optimal design problem for some wavelet regression models. Wavelets are very flexible in modeling complex relations, and optimal designs are appealing as a means of increasing the experimental precision. In contrast to the designs for the Haar wavelet regression model (Herzberg and Traves 1994; Oyet and Wiens 2000), the I-optimal designs we construct are diffe...

random regression models (rrm) have become common for the analysis of longitudinal data or repeated records on individual over time. the goal of this paper was to explore the use of random regression models with orthogonal / legendre polynomials (rrl) to analyze new repeated measures called clutch size (cs) as a meristic trait for iranian native fowl. legendre polynomial functions of increasing...

We prove that the Toeplitz binary value matrix inversion associated with mth order E-spline interpolation can be implemented using only 2 (m + 1) additions. We develop pipelined architectures for real time B-spline interpolation based on simple running average filters. We also show that an ideal interpolating function, which is approximated by a truncated sinc function with M half cycles, can b...

We consider the problem of modeling the mean function in regression. Often there is enough knowledge to model some components of the mean function parametrically. But for other vague and/or nuisance components, it is often desirable to leave them unspecified and to be modeled nonparametrically. In this article, we propose a general class of smoothing spline semi-parametric nonlinear regression ...

Sharia Bank Return On Assets (ROA) modeling in Indonesia 2018 aims to analyze the relationship pattern of Retturn with interest rates. The analysis that is often used for regression analysis. Regression divided into two, namely parametric and nonparametric. most commonly nonparametric methods are kernel spline regression. In this study, was Nadaraya-Watson (NWE) estimator Local Polynomial (LPE)...