**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**3077

# Search results for: linear trend estimation

##### 3077 The Relative Efficiency of Parameter Estimation in Linear Weighted Regression

**Authors:**
Baoguang Tian,
Nan Chen

**Abstract:**

A new relative efficiency in linear model in reference is instructed into the linear weighted regression, and its upper and lower bound are proposed. In the linear weighted regression model, for the best linear unbiased estimation of mean matrix respect to the least-squares estimation, two new relative efficiencies are given, and their upper and lower bounds are also studied.

**Keywords:**
Linear weighted regression,
Relative efficiency,
Mean matrix,
Trace.

##### 3076 An Estimation of Variance Components in Linear Mixed Model

**Authors:**
Shuimiao Wan,
Chao Yuan,
Baoguang Tian

**Abstract:**

**Keywords:**
Linear mixed model,
Random effects,
Parameter
estimation,
Stein function.

##### 3075 Variogram Fitting Based on the Wilcoxon Norm

**Authors:**
Hazem Al-Mofleh,
John Daniels,
Joseph McKean

**Abstract:**

**Keywords:**
Non-Linear Wilcoxon,
robust estimation,
Variogram
estimation.

##### 3074 Validation of the Linear Trend Estimation Technique for Prediction of Average Water and Sewerage Charge Rate Prices in the Czech Republic

**Authors:**
Aneta Oblouková,
Eva Vítková

**Abstract:**

The article deals with the issue of water and sewerage charge rate prices in the Czech Republic. The research is specifically focused on the analysis of the development of the average prices of water and sewerage charge rate in the Czech Republic in 1994-2021 and on the validation of the chosen methodology relevant for the prediction of the development of the average prices of water and sewerage charge rate in the Czech Republic. The research is based on data collection. The data for this research were obtained from the Czech Statistical Office. The aim of the paper is to validate the relevance of the mathematical linear trend estimate technique for the calculation of the predicted average prices of water and sewerage charge rates. The real values of the average prices of water and sewerage charge rates in the Czech Republic in 1994-2018 were obtained from the Czech Statistical Office and were converted into a mathematical equation. The same type of real data was obtained from the Czech Statistical Office for 2019-2021. Prediction of the average prices of water and sewerage charge rates in the Czech Republic in 2019-2021 was also calculated using a chosen method – a linear trend estimation technique. The values obtained from the Czech Statistical Office and the values calculated using the chosen methodology were subsequently compared. The research result is a validation of the chosen mathematical technique to be a suitable technique for this research.

**Keywords:**
Czech Republic,
linear trend estimation,
price prediction,
water and sewerage charge rate.

##### 3073 Two New Relative Efficiencies of Linear Weighted Regression

**Authors:**
Shuimiao Wan,
Chao Yuan,
Baoguang Tian

**Abstract:**

**Keywords:**
Linear weighted regression,
Relative efficiency,
Lower bound,
Parameter estimation.

##### 3072 Bi-linear Complementarity Problem

**Authors:**
Chao Wang,
Ting-Zhu Huang Chen Jia

**Abstract:**

In this paper, we propose a new linear complementarity problem named as bi-linear complementarity problem (BLCP) and the method for solving BLCP. In addition, the algorithm for error estimation of BLCP is also given. Numerical experiments show that the algorithm is efficient.

**Keywords:**
Bi-linear complementarity problem,
Linear complementarity
problem,
Extended linear complementarity problem,
Error
estimation,
P-matrix,
M-matrix.

##### 3071 Stochastic Estimation of Cavity Flowfield

**Authors:**
Yin Yin Pey,
Leok Poh Chua,
Wei Long Siauw

**Abstract:**

**Keywords:**
Open cavity,
Particle Image Velocimetry,
Stochastic
estimation,
Turbulent kinetic energy.

##### 3070 Density Estimation using Generalized Linear Model and a Linear Combination of Gaussians

**Authors:**
Aly Farag,
Ayman El-Baz,
Refaat Mohamed

**Abstract:**

In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.

**Keywords:**
Logistic regression model,
Expectationmaximization,
Segmentation.

##### 3069 A Comparison of the Sum of Squares in Linear and Partial Linear Regression Models

**Authors:**
Dursun Aydın

**Abstract:**

**Keywords:**
Partial Linear Regression Model,
Linear RegressionModel,
Residuals,
Deviance,
Smoothing Spline.

##### 3068 Kalman Filter Gain Elimination in Linear Estimation

**Authors:**
Nicholas D. Assimakis

**Abstract:**

In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.

**Keywords:**
Discrete time,
linear estimation,
Kalman filter,
Kalman filter gain.

##### 3067 Orthogonal Regression for Nonparametric Estimation of Errors-in-Variables Models

**Authors:**
Anastasiia Yu. Timofeeva

**Abstract:**

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

**Keywords:**
Grade point average,
orthogonal regression,
penalized regression spline,
locally weighted regression.

##### 3066 Design of Nonlinear Observer by Using Augmented Linear System based on Formal Linearization of Polynomial Type

**Authors:**
Kazuo Komatsu,
Hitoshi Takata

**Abstract:**

The objective of this study is to propose an observer design for nonlinear systems by using an augmented linear system derived by application of a formal linearization method. A given nonlinear differential equation is linearized by the formal linearization method which is based on Taylor expansion considering up to the higher order terms, and a measurement equation is transformed into an augmented linear one. To this augmented dimensional linear system, a linear estimation theory is applied and a nonlinear observer is derived. As an application of this method, an estimation problem of transient state of electric power systems is studied, and its numerical experiments indicate that this observer design shows remarkable performances for nonlinear systems.

**Keywords:**
nonlinear system,
augmented linear system,
nonlinear observer,
formal linearization,
electric power system.

##### 3065 Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method

**Authors:**
Cheng Zhang,
James Marco,
Walid Allafi,
Truong Q. Dinh,
W. D. Widanage

**Abstract:**

**Keywords:**
Equivalent circuit model,
continuous time domain
estimation,
linear integral filter method,
parameter and SOC
estimation,
recursive least square.

##### 3064 Effect of Channel Estimation on Capacity of MIMO System Employing Circular or Linear Receiving Array Antennas

**Authors:**
Xia Liu,
Marek E. Bialkowski

**Abstract:**

**Keywords:**
MIMO,
channel capacity,
channel estimation,
ULA,
UCA,
spatial correlation

##### 3063 Localization of Near Field Radio Controlled Unintended Emitting Sources

**Authors:**
Nurbanu Guzey,
S. Jagannathan

**Abstract:**

Locating Radio Controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

**Keywords:**
Localization,
angle of arrival (AoA),
range
estimation,
array signal processing,
ESPRIT,
uniform linear array
(ULA).

##### 3062 Estimation of Load Impedance in Presence of Harmonics

**Authors:**
Khaled M. EL-Naggar

**Abstract:**

This paper presents a fast and efficient on-line technique for estimating impedance of unbalanced loads in power systems. The proposed technique is an application of a discrete timedynamic filter based on stochastic estimation theory which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signal. The non-linear load impedance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition to the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional static estimation methods such as the least error square method.

**Keywords:**
Estimation,
identification,
Harmonics,
Dynamic Filter.

##### 3061 Sensitivity Analysis for Direction of Arrival Estimation Using Capon and Music Algorithms in Mobile Radio Environment

**Authors:**
Mustafa Abdalla,
Khaled A. Madi,
Rajab Farhat

**Abstract:**

**Keywords:**
Antenna array,
Capon,
MUSIC,
Direction-of-arrival estimation,
signal processing,
uniform linear arrays.

##### 3060 Evaluation of Model Evaluation Criterion for Software Development Effort Estimation

**Authors:**
S. K. Pillai,
M. K. Jeyakumar

**Abstract:**

Estimation of model parameters is necessary to predict the behavior of a system. Model parameters are estimated using optimization criteria. Most algorithms use historical data to estimate model parameters. The known target values (actual) and the output produced by the model are compared. The differences between the two form the basis to estimate the parameters. In order to compare different models developed using the same data different criteria are used. The data obtained for short scale projects are used here. We consider software effort estimation problem using radial basis function network. The accuracy comparison is made using various existing criteria for one and two predictors. Then, we propose a new criterion based on linear least squares for evaluation and compared the results of one and two predictors. We have considered another data set and evaluated prediction accuracy using the new criterion. The new criterion is easy to comprehend compared to single statistic. Although software effort estimation is considered, this method is applicable for any modeling and prediction.

**Keywords:**
Software effort estimation,
accuracy,
Radial Basis
Function,
linear least squares.

##### 3059 A Linear Use Case Based Software Cost Estimation Model

**Authors:**
Hasan.O. Farahneh,
Ayman A. Issa

**Abstract:**

Software development is moving towards agility with use cases and scenarios being used for requirements stories. Estimates of software costs are becoming even more important than before as effects of delays is much larger in successive short releases context of agile development. Thus, this paper reports on the development of new linear use case based software cost estimation model applicable in the very early stages of software development being based on simple metric. Evaluation showed that accuracy of estimates varies between 43% and 55% of actual effort of historical test projects. These results outperformed those of wellknown models when applied in the same context. Further work is being carried out to improve the performance of the proposed model when considering the effect of non-functional requirements.

**Keywords:**
Metrics,
Software Cost Estimation,
Use Cases

##### 3058 Robust Adaptive Observer Design for Lipschitz Class of Nonlinear Systems

**Authors:**
M. Pourgholi,
V.J.Majd

**Abstract:**

This paper addresses parameter and state estimation problem in the presence of the perturbation of observer gain bounded input disturbances for the Lipschitz systems that are linear in unknown parameters and nonlinear in states. A new nonlinear adaptive resilient observer is designed, and its stability conditions based on Lyapunov technique are derived. The gain for this observer is derived systematically using linear matrix inequality approach. A numerical example is provided in which the nonlinear terms depend on unmeasured states. The simulation results are presented to show the effectiveness of the proposed method.

**Keywords:**
Adaptive observer,
linear matrix inequality,
nonlinear systems,
nonlinear observer,
resilient observer,
robust estimation.

##### 3057 Applying Gibbs Sampler for Multivariate Hierarchical Linear Model

**Authors:**
Satoshi Usami

**Abstract:**

Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.

**Keywords:**
Gibbs sampler,
Hierarchical Linear Model,
Markov Chain Monte Carlo,
Multivariate Hierarchical Linear Model

##### 3056 A Study on a Research and Development Cost-Estimation Model in Korea

**Authors:**
Babakina Alexandra,
Yong Soo Kim

**Abstract:**

In this study, we analyzed the factors that affect research funds using linear regression analysis to increase the effectiveness of investments in national research projects. We collected 7,916 items of data on research projects that were in the process of being finished or were completed between 2010 and 2011. Data pre-processing and visualization were performed to derive statistically significant results. We identified factors that affected funding using analysis of fit distributions and estimated increasing or decreasing tendencies based on these factors.

**Keywords:**
R&D funding,
Cost estimation,
Linear regression,
Preliminary feasibility study.

##### 3055 Algebraic Approach for the Reconstruction of Linear and Convolutional Error Correcting Codes

**Authors:**
Johann Barbier,
Guillaume Sicot,
Sebastien Houcke

**Abstract:**

In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.

**Keywords:**
Blind estimation parameters,
error correcting codes,
non-cooperative context,
reconstruction algorithm

##### 3054 Model-Based Small Area Estimation with Application to Unemployment Estimates

**Authors:**
Hichem Omrani,
Philippe Gerber,
Patrick Bousch

**Abstract:**

The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.

**Keywords:**
Small area estimation,
statistical method,
sampling,
empirical best linear unbiased predictor (EBLUP),
decision-making.

##### 3053 A Diffusion Least-Mean Square Algorithm for Distributed Estimation over Sensor Networks

**Authors:**
Amir Rastegarnia,
Mohammad Ali Tinati,
Azam Khalili

**Abstract:**

In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.

**Keywords:**
Adaptive filter,
distributed estimation,
sensor network,
diffusion.

##### 3052 Design of a Non-linear Observer for VSI Fed Synchronous Motor

**Authors:**
P. Ramana ,
K. Alice Mary,
M. Surya Kalavathi,
M. Phani Kumar

**Abstract:**

**Keywords:**
Permanent magnet synchronous motor,
Mathematicalmodelling,
Rotor reference frame,
parameter estimation,
Luenbergerobserver,
reduced order observer,
full order observer

##### 3051 On Best Estimation for Parameter Weibull Distribution

**Authors:**
Hadeel Salim Alkutubi

**Abstract:**

The objective of this study is to introduce estimators to the parameters and survival function for Weibull distribution using three different methods, Maximum Likelihood estimation, Standard Bayes estimation and Modified Bayes estimation. We will then compared the three methods using simulation study to find the best one base on MPE and MSE.

**Keywords:**
Maximum Likelihood estimation ,
Bayes estimation,
Jeffery prior information,
Simulation study

##### 3050 Novel GPU Approach in Predicting the Directional Trend of the S&P 500

**Authors:**
A. J. Regan,
F. J. Lidgey,
M. Betteridge,
P. Georgiou,
C. Toumazou,
K. Hayatleh,
J. R. Dibble

**Abstract:**

Our goal is development of an algorithm capable of predicting the directional trend of the Standard and Poor’s 500 index (S&P 500). Extensive research has been published attempting to predict different financial markets using historical data testing on an in-sample and trend basis, with many authors employing excessively complex mathematical techniques. In reviewing and evaluating these in-sample methodologies, it became evident that this approach was unable to achieve sufficiently reliable prediction performance for commercial exploitation. For these reasons, we moved to an out-ofsample strategy based on linear regression analysis of an extensive set of financial data correlated with historical closing prices of the S&P 500. We are pleased to report a directional trend accuracy of greater than 55% for tomorrow (t+1) in predicting the S&P 500.

**Keywords:**
Financial algorithm,
GPU,
S&P 500,
stock market
prediction.

##### 3049 Trend Analysis of Annual Total Precipitation Data in Konya

**Authors:**
Naci Büyükkaracığan

**Abstract:**

**Keywords:**
Trend analysis,
precipitation,
hydroclimatology,
Konya,
Turkey.

##### 3048 Orthogonal Polynomial Density Estimates: Alternative Representation and Degree Selection

**Authors:**
Serge B. Provost,
Min Jiang

**Abstract:**

**Keywords:**
kernel density estimation,
orthogonal polynomials,
moment-based methodologies,
density approximation.