Testing for Higher Order Serial Correlation in Regression Equations when the Regressors Include Lagged Dependent Variables

Econometrica ◽  
1978 ◽  
Vol 46 (6) ◽  
pp. 1303 ◽  
Author(s):  
L. G. Godfrey
Keyword(s):  
Serial Correlation ◽  
Higher Order ◽  
Regression Equations ◽  
Dependent Variables

scholarly journals Pengaruh Motivasi dan Disiplin Kerja terhadap Kinerja Pegawai pada Badan Pengelola Pajak dan Restribusi Daerah Muaro Jambi

2020 ◽  
Vol 10 (2) ◽  
pp. 109
Author(s):  
Endang Dofitria Angraini
Keyword(s):  
Quantitative Analysis ◽  
Job Performance ◽  
Positive Relationship ◽  
Regression Equations ◽  
Independent Variables ◽  
Tax Management ◽  
Dependent Variables ◽  
Home Work ◽  
High Motivation ◽  
Test Correlation

This reseach was  to analyse how the effect of motivation and dicipline on job performance . How to as well as a condition of motivation, dicipline and job performance at the Tax Management and Restrition of Muaro  Jambi Area.The research methodology is descriptive and quantitative analysis methods. Data used is secondary data.The population become object in this research is job performance at Tax Management and Restrition of Muaro  Jambi Area. The method for analysis is analysis multifly regression, hypotesis test, correlation so determinant coefficient and F_tes so t_test. The object of this research is the Tax Management and Restrition of Muaro  Jambi Area. This office is a branch of Tax Management and Restrition of Muaro  Jambi Area, which is the task of collect tax on earth and buildings and other taxes in the Muaro Jambi area.Analysis on the research of respondents felt a high motivation and work discipline in the performance of tasks provided by the superiors. In the statement of respondents the indicator comes and home work on time shows the hihest score, which is a score of 280 verry high categories. Multiple linear regression equations are Y = 8,266 + 0.243X1 + 0.740X2 + E. Independent variables (motivation and work discipline) simultaneously have significant effect on the dependent variables (performance of members). While partial motivation affects performance and variable work discipline affects of the performance. Conclusion that the motivation and discipline have significant effect on performance and have a positive relationship in Tax Management and Restrition of Muaro  Jambi Area.

Rain Distribution in a Mountainous Watershed

1993 ◽  
Vol 24 (4) ◽  
pp. 225-242 ◽  
Author(s):  
A. Loukas ◽  
M.C. Quick
Keyword(s):  
The Other ◽  
Regression Equations ◽  
Watershed Model ◽  
Rainfall Events ◽  
Creek Watershed ◽  
Lower Elevation ◽  
Hourly Rainfall ◽  
Dependent Variables ◽  
Mountainous Watershed ◽  
Rainfall Depth

The orographic and temporal gradients of rainfall in a mountainous watershed in southwestern British Columbia have been analyzed and streamflow has been estimated using a watershed model. The study watershed is the Jamieson Creek watershed located approximately 30 km north of Vancouver in the Coastal Mountains. The purpose of the study was to determine whether rainfall follows a definable pattern in this mountainous watershed. Regression analysis has been performed for the total rainfall depth per event and hourly intensity for the period 1972-1975. Data is taken from the rainfall season of June to mid-November in order to avoid complications of combined rain and snow events. In this analysis, the rainfall data from a gauge at the lower elevation was used as the set of independent variables and the data from the other four gauges in the watershed as dependent variables. The results showed that the rainfall depth per event increased up to the mid-elevation of the watershed, and then decreased at the upper elevations. On the other hand, the hourly rainfall intensity was found to decrease with increase of elevation in the watershed, so that longer duration of rainfall events occurs at the middle and upper watershed. The regression equations, developed from the analysis of the distribution of the hourly intensity, were used for the prediction of rainfall events of the years 1976-1977. The agreement between the predicted and the observed rain was statistically good. Also, the simulation of the watershed streamflow using the predicted rainfall gave good results. Consequently, because the rainfall follows a definable distribution as a function of elevation, it is possible to use data from one station located at the lower elevation in combination with the developed predictor equations to accurately describe the rainfall over the watershed.

A New Family of Higher-Order Time Integration Algorithms for the Analysis of Structural Dynamics

2017 ◽  
Vol 84 (7) ◽  
Author(s):  
Wooram Kim ◽  
J. N. Reddy
Keyword(s):  
Structural Dynamics ◽  
Time Integration ◽  
Higher Order ◽  
Weighted Residual Method ◽  
New Family ◽  
Equal Degree ◽  
Fundamental Limitations ◽  
Mixed Formulations ◽  
Dependent Variables ◽  
Integration Algorithms

For the development of a new family of implicit higher-order time integration algorithms, mixed formulations that include three time-dependent variables (i.e., the displacement, velocity, and acceleration vectors) are developed. Equal degree Lagrange type interpolation functions in time are used to approximate the dependent variables in the mixed formulations, and the time finite element method and the modified weighted-residual method are applied to the velocity–displacement and velocity–acceleration relations of the mixed formulations. Weight parameters are introduced and optimized to achieve preferable attributes of the time integration algorithms. Specific problems of structural dynamics are used in the numerical examples to discuss some fundamental limitations of the well-known second-order accurate algorithms as well as to demonstrate advantages of using the developed higher-order algorithms.

scholarly journals Use of Modern Regression Analysis in the Dielectric Properties of Foods

Foods ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1472
Author(s):  
Yu-Kai Weng ◽  
Jiunyuan Chen ◽  
Ching-Wei Cheng ◽  
Chiachung Chen
Keyword(s):  
Regression Analysis ◽  
Dielectric Properties ◽  
Influencing Factors ◽  
Polynomial Regression ◽  
Treatment Method ◽  
Regression Equations ◽  
Constant Variance ◽  
Dependent Variables ◽  
Qualitative Variables ◽  
The Relationship

The dielectric properties of food materials is used to describe the interaction of foods with electromagnetic energy for food technology and engineering. To quantify the relationship between dielectric properties and influencing factors, regression analysis is used in our study. Many linear or polynomial regression equations are proposed. However, the basic assumption of the regression analysis is that data with a normal distribution and constant variance are not checked. This study uses sixteen datasets from the literature to derive the equations for dielectric properties. The dependent variables are the dielectric constant and the loss factor. The independent variables are the frequency, temperature, and moisture content. The dependent variables and frequency terms are transformed for regression analysis. The effect of other qualitative factors, such as treatment method and the position of subjects on dielectric properties, are determined using categorical testing. Then, the regression equations can be used to determine which influencing factors are important and which are not. The method can be used for other datasets of dielectric properties to classify influencing factors, including quantitative and qualitative variables.

scholarly journals Effects of Coniophora puteana (Schumach.) P. Karst. Fungus on the decomposition of sessile oak wood

2016 ◽  
pp. 37-47
Author(s):  
Miroslava Marković ◽  
Snežana Rajković
Keyword(s):  
Mass Loss ◽  
Compression Strength ◽  
Brown Rot ◽  
Regression Equations ◽  
Initial Value ◽  
Oak Wood ◽  
Sessile Oak ◽  
Coniophora Puteana ◽  
Dependent Variables ◽  
Independent Variable

The paper examines the effects of a brown rot agent-Coniophora puteana (Schumach.) P. Karst on the mass loss and compression strength of sessile oak (Q. petraea agg) wood. The wood mass loss of Q. petraea agg., caused by C. puteana amounted to 1.5, 2.12 and 2.23 after 2, 4 and 6 months respectively. The obtained values indicate that the biggest mass loss of wood occurred in the first two months. Compression strength also decreased under the influence of C. puteana. In comparison to its initial value (100%), it amounted to 92.13, 90.72 and 76.25 after 2, 4 and 6 months. The analysis of the correlation between the sessile oak mass loss-G m and compression strength decrease- p (dependent variables) and the incubation time (T-independent variable) revealed a strong correlation between the variables and the following regression equations were obtained: G m = 0.0638492 + 0.954107 x T  p = 96.328-2.666 x T

scholarly journals On the internal approach to differential equations 3. Infinitesimal symmetries

2016 ◽  
Vol 66 (6) ◽  
Author(s):  
Veronika Chrastinová ◽  
Václav Tryhuk
Keyword(s):  
Partial Differential Equations ◽  
Differential Equations ◽  
Linear Approximation ◽  
Higher Order ◽  
Geometrical Theory ◽  
Partial Differential ◽  
Absolute Sense ◽  
Dependent Variables ◽  
The Absolute

AbstractThe geometrical theory of partial differential equations in the absolute sense, without any additional structures, is developed. In particular the symmetries need not preserve the hierarchy of independent and dependent variables. The order of derivatives can be changed and the article is devoted to the higher-order infinitesimal symmetries which provide a simplifying “linear approximation” of general groups of higher-order symmetries. The classical Lie’s approach is appropriately adapted.

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