Ordinary Least-squares Method Research Articles

Including experimental uncertainty on the independent variables when modelling microbial dynamics: The combined effect of pH and acetic acid on the growth rate of E. coli K12

Modelling methods applied in predictive microbiology generally neglect the importance of uncertainty on the measurement of the independent variables. The Ordinary Least Squares (OLS) method that is commonly applied in predictive microbiology is only applicable if the experimental error on the inputs of the model are insignificant. However, this does not apply for many types of experimental measurements of the independent variables. Therefore, a parameter estimation method was adapted in this research for the estimation of the parameters of secondary models, taking into account uncertainty on the measurement of the influencing food characteristics. This parameter estimation method was based on the work of Stortelder (1996) and is referred to as the Weighted Total Least Squares method (WTLS). The method is formulised as an extension of the commonly used OLS method. Consequently the current WTLS method (i) is easily implemented using similar numerical methods, (ii) reduces to an OLS method when the measurement error on the model inputs is negligible and (iii) enables the evaluation of the accuracy of the model parameter estimates based on the same approximations.

Estimating Two Heat-Conduction Parameters From Two Complementary Transient Experiments

A desirable feature of any parameter estimation method is to obtain as much information as possible with one experiment. However, achieving multiple objectives with one experiment is often not possible. In the field of thermal parameter estimation, a determination of thermal conductivity, volumetric heat capacity, heat addition rate, surface emissivity, and convection coefficient may be desired from a set of temperature measurements in an experiment where a radiant heat source is used. It would not be possible to determine all of these parameters from such an experiment; more information would be needed. The work presented in the present research shows how thermal parameters can be determined from temperature measurements using complementary experiments where the same material is tested more than once using a different geometry or heating configuration in each experiment. The method of ordinary least squares is used in order to fit a mathematical model to a temperature history in each case. Several examples are provided using one-dimensional conduction experiments, with some having a planar geometry and some having a cylindrical geometry. The parameters of interest in these examples are thermal conductivity and volumetric heat capacity. Sometimes, both of these parameters cannot be determined simultaneously from one experiment but utilizing two complementary experiments may allow each of the parameters to be determined. An examination of confidence regions is an important topic in parameter estimation and this aspect of the procedure is addressed in the present work. A method is presented as part of the current research by which confidence regions can be found for results from a single analysis of multiple experiments.

ANALISIS PENGARUH INDEKS PEMBANGUNAN MANUSIA, PDRB PER KAPITA, DAN JUMLAH PENGANGGURAN TERHADAP JUMLAH PENDUDUK MISKIN DI PROVINSI JAMBI

Poverty is a problem faced by all countries in the world, especially the developing countries, such as Indonesia. Poverty is a complex issue that is affected by a variety of interrelated factors, such as people's income levels, unemployment, health, education, access to goods and services, geographic location, gender, and location the environment. The number of poor population in Central Java is relatively lebihtinggi compared to laindi province of Indonesia, that is occupying ranked second in the number of poor population the largest in Indonesia after East Java. This research aims to analyze how and how much the variable influences the human development index, GDP per capita, and the number of poor population against unemployment in Jambi province in the year 2016. Methods of analysis in this study using multiple linear regression analysis with the method of Ordinary Least Square (OLS) that use data between spaces (cross section) district/town in Jambi province year 2016 with the help of software Eviews 4.1. The results of this research indicate that the variable is the human development index (HDI) a negative and significant effect against the poor population in the province of Jambi, the per capita GDP is negative and significant effect against the number of poor population in The province of Jambi, the unemployment and the number of positive and significant effect against the poor population in the province of Jambi.Keywords: population of the poor, the human development index (HDI), GDP per capita, and the number of Unemployed

Determinant Analysis of Decrease In Manufacturing Export Value Amid Depreciation of Rupiah Exchange Rate

Indonesia uses a system of floating exchange rate. The depreciation of the exchange rate, in which the value of domestic currency decreases and the value of foreign currency increases, will increase the export. The high depreciation of Rupiah should be able to increase the competitiveness of Indonesia’s export products, especially the manufacturing exports that have the greatest contribution to the total exports. However, what has happened in recent years is very different. The depreciation of Rupiah value cannot spur the value of Indonesia’s manufacturing exports. Based on the fact above, the research is entitled "Determinant Analysis of Decrease in Manufacturing Export Value amid Depreciation of Rupiah Exchange Rate. This research uses time series secondary data for the quarterly period of 2006Q1-201Q3 that is obtained from Bank Indonesia, International Financial Statistics, and World Bank. The analytical technique used is the OLS (Ordinary Least Square) method using E-Views 6. The results of this research indicate that the Rupiah exchange rate and the GDP growth of the export destination countries have a positive relationship but are insignificant to the manufacturing exports, while the inflation rate is negative and insignificant to the value of manufacturing exports. Meanwhile, the raw material import has a significant positive effect on manufacturing exports. This shows that the Indonesia’s manufacturing exports still depend on the imported raw materials. Related to this fact, the government must take a strategic step in the short term to increase the non-oil exports, especially the exports of manufactured products that are the high value-added export products.

Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation

DNA methylation is a promising biomarker for forensic age prediction. A challenge that has emerged in recent studies is the fact that prediction errors become larger with increasing age due to interindividual differences in epigenetic ageing rates. This phenomenon of non-constant variance or heteroscedasticity violates an assumption of the often used method of ordinary least squares (OLS) regression. The aim of this study was to evaluate alternative statistical methods that do take heteroscedasticity into account in order to provide more accurate, age-dependent prediction intervals. A weighted least squares (WLS) regression is proposed as well as a quantile regression model. Their performances were compared against an OLS regression model based on the same dataset. Both models provided age-dependent prediction intervals which account for the increasing variance with age, but WLS regression performed better in terms of success rate in the current dataset. However, quantile regression might be a preferred method when dealing with a variance that is not only non-constant, but also not normally distributed. Ultimately the choice of which model to use should depend on the observed characteristics of the data.

Submerged Fixed Floating Structure under the Action of Surface Current

The implementation of floating structures has increased with the construction of new sluices for flood control. The overturning moment of floating structure and its influencing factors are the important parameters that determine the structural safety. It is essential to understand the overturning characteristics of these structures in currents. Based on hydrodynamic theory and equilibrium analysis, the hydraulic characteristics of a floating structure are discussed by means of theoretical analysis and experiments. A formula for the overturning moment is developed in terms of the time-averaged pressure on the structure. The corresponding parametric study aims to assess the effects of flow velocities, vertical positions, shape ratios and water levels on the overturning moment. The experimental results show that hydrodynamic factors have a significant influence on the overturning of the structure. Furthermore, a relationship is obtained between the overturning moment and the contributing parameters according to dimensional analysis and the linear fitting method of multidimensional ordinary least squares (OLS). The results predicted by the formula agree with the experimental results, demonstrating the potential for general applicability.

Monte Carlo simulation of ordinary least squares estimator through linear regression adaptive refined descriptive sampling algorithm

ABSTRACTThis paper shows the importance of the use of Monte Carlo experiments within Simple Linear Regression (SLR) Models through Refined Descriptive Sampling and proves practically that the asymptotic theory of the Ordinary Least Squares (OLS) estimator still hold with small samples when the Normality errors assumption is released. To this end, a simple Linear Regression adaptive Refined Descriptive Sampling (L2RDS) algorithm is proposed to estimate the parameter of SLR models by OLS method and computes its properties. Real data are used to properly specified the simulation model. The results show that L2RDS algorithm provides accurate and efficient point estimates.

Partially Adaptive Econometric Methods and the Modern Obesity Epidemic

Assumptions about explanatory variables and errors are central in regression analysis. For example, the well-known method of ordinary least squares yields consistent and efficient estimators if the underlying error terms are independently, identically, and normally distributed. Additionally, the conditional distribution of the dependent variable is symmetric. The modern obesity epidemic is a well-known health dilemma where the BMI distribution was initially positively skewed but has become more symmetric, which may affect inferences about health and public resource allocation. This study applies partially adaptive estimation methods with flexible error distributions to account for possible skewness and leptokurtosis in the distribution of BMI.

Relación entre propiedad intelectual, innovación y desarrollo: evidencias de datos de panel

En este trabajo se presentan los resultados de un análisis de datos de panel que explora la relación entre propiedad intelectual, innovación y desarrollo. Esta relación es abordada como una oportunidad para superar los desafíos que, en materia de crecimiento y desarrollo, tienen los países de renta media, como la República Dominicana. El panel de datos fue construido a partir de información procedente de distintas fuentes, desde 2005 hasta 2011. El análisis de los datos de panel se realizó en dos momentos: 1) mediante un análisis factorial de componentes principales, para definir los factores de mayor peso en la explicación de la varianza del panel de datos, y 2) utilizando el método de mínimos cuadrados ordinarios, para estimar la relación entre propiedad intelectual, innovación y desarrollo. Los resultados mostrados por los datos de panel destacan que los factores de capital humano, los sistemas de propiedad intelectual, como expresión del grado de desarrollo institucional de las economías, y el esfuerzo en producción de conocimiento e innovación son factores claves en el desempeño y en las dinámicas de crecimiento y desarrollo. Se concluye que el fortalecimiento institucional de los sistemas de propiedad intelectual como pilar de los sistemas de innovación, así como la inversión en ciencia, tecnología e innovación constituyen estrategias viables para promover el crecimiento económico y la salida de la trampa de los ingresos medios en economías como la de República Dominicana.

Dealing with Outlier in Linear Calibration Curves: A Case Study of Graphite Furnace Atomic Absorption Spectrometry

Outlier in the calibration of lead by graphite furnace atomic absorption spectrometry (GF-AAS) has been studied with help of the statistical tool F-test and T-test. The process consisted on measuring five standard solutions with three replicate to prepare the calibration curve. Ordinary least squares method (OLSM) was used to get the equation of the linear calibration curve; the correlation coefficient R² and analysis of variance (ANOVA) was used to validate the linearity of this calibration curve. Proceeding to the graphic representation and the residual plot of the calibration, a suspected outlier was found. The statistical tool F-test and T-test were used to examine the suspected outlier, they yield the same result and confirm the outlier data. The calibration curve with and without the outlier data were taken care to investigate the effect of this outlier in the limit of detection (LOD), limit of quantification (LOQ), the concentration of lead in the fourteen samples and the uncertainty related to calibration curve. It has been observed that the linearity of the calibration curve is accepted for both cases. For the case of the calibration with the outlier, the estimated LOD and LOQ were 1.76 µg L-1 and 5.18 µg L-1, respectively. The concentrations of lead in the sample are between 2.85 µg L-1 and 22.61µg L-1 and the uncertainty related to calibration curve vary between 1.17µg L-1 and 1.41 µg L-1. On the other hand, for the calibration without the outlier data, the value of LOD and LOQ were improved compared to the previous value, the value of these two parameters were 1.32 µg L-1 and 3.96 µg L-1, respectively. The concentration of lead in the sample vary between 2.75 µg L-1 and 22.52 µg L-1, compared to the previous concentration these value decrease from 0.40% and 3.29%. The uncertainties related to calibration curve vary between 0.90 µg L-1 and 1.09 µg L-1 for the second case, compared to the uncertainty in the first case, the uncertainty decreases from 22.48% to 23.53%. In conclusion, dealing with outlier improves the quality of the measurement and allow producing a reliable analytical data.

АНАЛИЗ ТОЧНОСТИ МОДЕЛЬНЫХ ЭКСПЕРИМЕНТОВ ПО ПОГРУЖЕНИЮ МОДЕЛЕЙ КОШЕЛЬКОВОГО НЕВОДА ПРИ УСЛОВИИ БОКОВОГО ТЕЧЕНИЯ

The research aim is to analyze accuracy of the experimental data obtained during the experiments in the hydraulic channel of "MariNPO", LLC (Kaliningrad) in 2014. During the experiments, three purse seine models were immersed under different loading of a leadline (0 kg, 0.248 kg, 0.338 kg) and different speed of the current (0.2 m/s, 0.3 m/s, 0.4 m/s). Seven experiments were carried out for each model (0 kg and 0.2 m/s; 0.248 kg and 0.2, 0.3, 0.4 m/s; 0.338 kg and 0.2, 0.3, 0.4 m/s). To confirm reliability of the data there was carried out the analysis of the total error which included: instrumental error, cargo error, measurement error of the net the models were made of, inaccuracy of immersion, displacement of the seine along OY axis, approximation error. To approximate the pilot data there was chosen the method of ordinary least squares. Approximation was conducted with a straight line (linear regression), polynomial n (polynomial regression), and a combination of arbitrary functions. The least error (6.82%) was obtained in the experiment 0 kg and 0.3 m/s, maximum (14.76%) - in the experiment 0.338 kg and 0.2 m/s. When the error doesn’t exceed 15%, subject to the adequate precision of measurement, the results of the experiments should be considered satisfactory.

Análisis de la dolarización y sus efectos sobre la inversión extranjera directa en Ecuador. Periodo 2000 - 2016

El presente artículo se enfoca en las consecuencias que ha tenido la implementación de la dolarización en la economía ecuatoriana y a su vez, las repercusiones de ésta sobre las decisiones de los inversionistas extranjeros, la metodología de investigación utilizada para el análisis de la dolarización se realizó a través de las variables macroeconómicas más importantes con relación a la inversión extranjera directa, los resultados de la estimación del modelo econométrico se los obtuvo mediante una regresión lineal múltiple, estimada por el método de mínimos cuadrados ordinarios. Se demuestra que la dolarización, medida a través de los indicadores: inversión en electricidad, índice de precios al consumidor, salario básico unificado, gasto en educación y PIB tienen una relación directa con la inversión extranjera directa. Palabras clave: Dolarización, inversión extranjera directa, salario básico unificado, gasto en educación, producto interno bruto. URL: http://revistas.uta.edu.ec/erevista/index.php/bcoyu/article/view/652

Substitution of Formal and Informal Home Care Service Use and Nursing Home Service Use: Health Outcomes, Decision-Making Preferences, and Implications for a Public Health Policy.

The purposes of this study are: (1) to empirically identify decision-making preferences of long-term health-care use, especially informal and formal home care (FHC) service use; (2) to evaluate outcomes vs. costs based on substitutability of informal and FHC service use; and (3) to investigate health outcome disparity based on substitutability. The methods of ordinary least squares, a logit model, and a bivariate probit model are used by controlling for socioeconomic, demographic, and physical/mental health factors to investigate outcomes and costs based substitutability of informal and formal health-care use. The data come from the 2013 Japanese Study of Aging and Retirement (JSTAR), which is designed by Keizai-Sangyo Kenkyu-jo, Hitotsubashi University, and the University of Tokyo. The JSTAR is a globally comparable data survey of the elderly. There exists a complement relationship between the informal home care (IHC) and community-based FHC services, and the elasticity's ranges from 0.18 to 0.22. These are reasonable results, which show that unobservable factors are positively related to IHC and community-based FHC, but negatively related to nursing home (NH) services based on our bivariate probit model. Regarding health-care outcome efficiency issue, the IHC is the best one among three types of elderly care: IHC, community-based FHC, and NH services. Health improvement/outcome of elderly with the IHC is heavier concentrated on IHC services than the elderly care services by community-based FHC and NH care services. Policy makers need to address a diversity of health outcomes and efficiency of services based on providing services to elderly through resource allocation to the different types of long-term care. A provision of partial or full compensation for elderly care at home is recommendable and a viable option to improve their quality of lives.

Shareholders wealth and mergers and acquisitions (M&As)

We re-examine the abnormal returns (ARs) around merger announcements using a large sample of 8,945 announcements. We estimate the ARs using the Carhart (1997) four-factor model under the standard ordinary least square (OLS) method and the Glosten et al.’s (1993) asymmetric GARCH specification (hereafter, GJR-GARCH). Under the OLS method, acquirers do not generate significant cumulative ARs (CARs) in line with prior work. Our new results, however, show that under the GJR-GARCH estimation, acquirers generate positive and significant cumulative CARs. We attribute the gains to the use of the GJR-GARCH estimation method, as the GJR-GARCH method is more effective in capturing conditional volatility and asymmetry in the excess returns.

Developing accident prediction model for railway level crossings

Railway level crossing (LX) safety continues to be one of the most critical issues for railways, despite an ever-increasing focus on improving design and application practices. Accidents at European LXs account for about one-third of the entire railway accidents and result in more than 300 deaths every year in Europe. Due to the non-deterministic causes, the complex operation background and the lack of thorough statistical analysis based on accident/incident data, the risk assessment of LXs remains a challenging task. In the present paper, some LX accident prediction models are developed. Such models allow for highlighting the influence of the main impacting parameters, i.e., the average daily road traffic, the average daily railway traffic, the annual road accidents, the vertical road profile, the horizontal road alignment, the road width, the crossing length, the railway speed limit and the geographic region. The Ordinary Least-Squares (OLS) and Nonlinear Least-Squares (NLS) methods are employed to estimate the respective coefficients of variables in the prediction models, based on the LX accident/incident data. The validation and comparison process is performed through statistical means to examine how well the estimation of the models fits the reality. The outcomes of validation and comparison attest that the improved accident prediction model has statistic-based approbatory quality. Moreover, the improved accident prediction model combined with the NB distribution shows relatively high predictive accuracy of the probability of accident occurrence.

Forecasting Completed Cost of Highway Construction Projects Using LASSO Regularized Regression

Finishing highway projects within budget is critical for state highway agencies (SHAs) because budget overruns can result in severe damage to their reputation and credibility. Cost overruns in highway projects have plagued public agencies globally. Hence, this research aims to develop a parametric cost estimation model for SHAs to forecast the completed project cost prior to project execution to take necessary measures to prevent cost escalation. Ordinary least square (OLS) regression has been a commonly used parametric estimation method in the literature. However, OLS regression has certain limitations. It, for instance, requires strict statistical assumptions. This paper proposes an alternative approach—least absolute shrinkage and selection operator (LASSO)—that has proved in other fields of research to be significantly better than the OLS method in many respects, including automatic feature selection, the ability to handle highly correlated data, ease of interpretability, and numerical stability of the model predictions. Another contribution to the body of knowledge is that this study simultaneously explores project-related variables with some economic factors that have not been used in previous research, but economic conditions are widely considered to be influential on highway construction costs. The data were separated into two groups: one for training the model and the other for validation purposes. Using the same dataset, both LASSO and OLS were used to build models, and then their performance was evaluated based on the mean absolute error, mean absolute percentage error, and root mean square error. The results showed that the LASSO regression model outperformed the OLS regression model based on the criteria.

Organizational capital, intellectual capital and cost stickiness (evidence from Iran)

PurposeThe purpose of this paper is to identify the relationship between organizational capital and the subsets of organizational capital (intellectual capital (IC)) cost and cost stickiness.Design/methodology/approachThis study is causal correlational research. The data related to the company’s financial statements were collected using the Rahavard Novin Software and www.rdis.ir. In this study, panel data were run with the use of Eviews 8, in order to test the hypotheses. The ordinary least-squares method is used in this study to estimate the parameters of the model.FindingsThe results obtained from the study show that there is a significant relationship between organizational capital and cost stickiness. However, there is no significant difference between high and low rank in terms of organizational capital and cost stickiness. In addition, there is a significant difference between IC and cost stickiness. Moreover, there is no significant difference between the components of IC and cost stickiness. Also, IC has an effect on the intensity of the relationship between organizational capital and cost stickiness.Originality/valueThis study explores the relationship between organizational capital and the subsets of IC and cost stickiness. Independent variables used in this study include organizational capital, IC and its components in the Pulic model, i.e. the efficiency of capital employed, the efficiency of human capital and the efficiency of structural capital.

PENGARUH PENANAMAN MODAL ASING, PERDAGANGAN INTERNASIONAL, GDP PER KAPITA, SEKTOR PERTANIAN, DAN URBANISASI TERHADAP PENDUDUK BEKERJA DI INDONESIA

This research aims to understand the influenceof foreign investment, international trade, Gross Domestic Product per capita, agriculture and urbanization of the working population. Country used as an object in this research is Indonesia. This research uses the method of analysis Ordinary Least Square (OLS) and the multiple linear regression analysis method. Research period are from 1997 – 2012. The results showed that the international trade, Gross Domestic Product per capita, agriculture and urbanization have significantpositive influenceon the population work in Indonesia, but foreign investment has no significanteffect on the working population in Indonesia.

Performance evaluation of the Ordinary Least Square (OLS) and Total Least Square (TLS) in adjusting field data: an empirical study on a DGPS data

Survey measurements have become the traditional means of obtaining point positions by most surveyors over the centuries. The assertion that a post processed DGPS field data is precise, accurate and can be used to execute any engineering works due to its minimum human errors need to be reviewed; this is because the post processed field data still contains errors and needs to be adjust. Adjustments and computations is one of the main research field in mathematical and satellite geodesy to assess the magnitude of errors and to study their distributions whether they are within or not within the acceptable tolerance. In order to achieve the objective of this study, a DGPS field data was adjusted using the Ordinary Least Square (OLS) and Total Least Square (TLS) techniques. The OLS considers errors only in the observation matrix, and adjusts observations in order to make the sum of its residuals minimum. The TLS considers errors in both the observation matrix and the data matrix, thereby minimizing the errors in both matrices. The limited availability of information on OLS and TLS in adjusting DGPS field data and the uncertainty of which method is optimal, whether the OLS and TLS is the most appropriate technique has called for the need to undertake this study. This study aimed at comparing the working efficiency of the OLS and TLS, assessing their individual accuracy and selecting the most effective method in adjusting DGPS field data. Each model was assessed based on statistical indicators of mean horizontal error (MHE), mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), and standard deviation (SD). After applying the OLS and TLS methods independently for the same datasets, it was ascertained that, the OLS method was better in adjusting DGPS field data than the TLS with a MHE and SD of +1.203079 m and +1.663134 m as compared to TLS with MHE and SD of +7.0985507 m and +2.594045 m respectively. This study will therefore create opportunity for geospatial professionals to know the efficiency of OLS and TLS in solving some of the problems in mathematical and satellite geodesy.Keywords: Differential Global Positioning, System, Total Least Square, Ordinary Least Square, Survey Adjustments, Horizontal Position Displacement

DETERMINATION OF DIRECTION TO RECONSTRUCTION OF GROUNDING SYSTEM

Purpose. In paper the most efficient and economical way for bringing the grounding system of power facilities into compliance with requirements of normative parameters was determined. Methodology. The determination was based on the comparison of the calculated values of touch voltage and length of additional electrodes for reconstruction of grounding system by two ways. To calculate the software based on the method of point current source which located in the three-layer soil, method guidance potential, Gauss method and the method of ordinary least squares was used. Results. For three possible cases amount of material and labor costs for the reconstruction and modernization of the grounding system while maintaining the equipotent grounding system and allowable touch voltage was defined. Originality. For the first time the effectiveness the reconstruction of grounding system for requirements of touch voltage, not to her of resistance, both in terms of electrical safety and in terms of material and labor costs proved. Practical value. The implementation of results saves a national scale funds for modernization and reconstruction of existing grounding systems of power facilities.