scholarly journals Probable values of rise and fall off time of solar cycles 23,24, and 25

1996 ◽  
Vol 39 (3) ◽  
Author(s):  
N. Ortiz de Adler ◽  
A. G. Elias
Keyword(s):  
Multiple Regression ◽  
Rise Time ◽  
Regression Method ◽  
Solar Cycles ◽  
Multiple Regression Method ◽  
Recurrence Tendency ◽  
Off Time ◽  
Good Agreement

From an analysis of the rise and fall off time of solar cycles 4 to 22, a recurrence tendency of 7 cycles is observed in the rise time and, apparently, of 9 cycles in the fall off time. The envelope of these times presents a decreasing amplitude of oscillation. According to this behaviour, the rise and fall length of future solar cycles until cycle 25 can be inferred qualitatively. These values are compared with those obtained with a multiple regression method showing a good agreement.

scholarly journals Analyzing and Predicating PH value in Nature Rubber Solidification Process Using Multiple Regression Method

2021 ◽  
Vol 1798 (1) ◽  
pp. 012005
Author(s):  
Zhongrui Sun ◽  
Bingbing Wang ◽  
Fan Zhang ◽  
Lusheng Liao ◽  
Weiguo Deng ◽  
...  
Keyword(s):  
Multiple Regression ◽  
Ph Value ◽  
Solidification Process ◽  
Regression Method ◽  
Multiple Regression Method

scholarly journals Calibration Curves by Means of Multiple Regression Method

1976 ◽  
Vol 92 (1056) ◽  
pp. 79-82
Author(s):  
Toshihiko ABE ◽  
Shin-ichi SUMI ◽  
Norio SANADA ◽  
Teruo SAKURAI ◽  
Osamu ASANO ◽  
...  
Keyword(s):  
Multiple Regression ◽  
Regression Method ◽  
Calibration Curves ◽  
Multiple Regression Method

scholarly journals Analysis of soil radon data in earthquake precursory studies

2014 ◽  
Vol 57 (5) ◽  
Author(s):  
Hari Prasad Jaishi ◽  
Sanjay Singh ◽  
Raghavendra Prasad Tiwari ◽  
Ramesh Chandra Tiwari
Keyword(s):  
Statistical Analysis ◽  
Multiple Regression ◽  
Radon Concentration ◽  
Seismic Activity ◽  
Meteorological Parameters ◽  
Regression Method ◽  
Seismic Zone ◽  
Type Ii ◽  
Soil Radon ◽  
Multiple Regression Method

<p>Soil radon data were recorded at two selected sites along Mat fault in Mizoram (India), which lies in the highest seismic zone in India. The study was carried out during July 2011 to May 2013 using LR-115 Type II films. Precursory changes in radon concentration were observed prior to some earthquakes that occurred around the measuring sites. Positive correlation was found between the measured radon data and the seismic activity in the region. Statistical analysis of the radon data together with the meteorological parameters was done using Multiple Regression Method. Results obtained show that the method employed was useful for removing the effect of meteorological parameters and to identify radon maxima possibly caused by seismic activity.</p>

scholarly journals Regional Spillover Effect Terhadap Pertumbuhan Ekonomi Kota Pekanbaru

2021 ◽  
Vol 4 (2) ◽  
pp. 621-634
Author(s):  
M. Irfan Rosyadi ◽  
Sinta Yulyanti
Keyword(s):  
Economic Growth ◽  
Multiple Regression ◽  
Economic Activity ◽  
Quantitative Methods ◽  
Spillover Effect ◽  
Secondary Data ◽  
Regression Method ◽  
Study Results ◽  
Multiple Regression Method ◽  
Spatial Impacts

The spillover effect of economic activity from one area to another is due to the inter-sector linkages, which have implications for economic growth. This study examines and presents empirical evidence on the effects of economic growth in the districts of Siak, Pelalawan, Kampar, Kuantan singingi, and Bengkalis, which have spatial impacts on the economic growth of Pekanbaru City. Through quantitative methods with secondary data from the Regency / City Central Statistics Agency in Riau Province, the data used is the Gross Regional Domestic Product from 2010 to 2019, then analyzed using the Multiple regression method. The study results show that Kampar, Kuantan singingi, Pelalawan, and Siak districts have a significant effect on the economic growth of Pekanbaru City, while Bengkalis does not affect. Not all of the natural resources owned by each district can provide a spillover effect of growth. However, a dominant sector in absorbing labor will provide a spillover effect of economic growth from one region to another. Keyword: Regional Spillover Effect. Economic Growht, Multiple Regression. Pekanbaru

Accuracy of the Multiple-Regression Method for Estimating Population-Density in Strip Transects

1986 ◽  
Vol 13 (2) ◽  
pp. 121 ◽  
Author(s):  
J Hone
Keyword(s):  
Population Density ◽  
Multiple Regression ◽  
Robust Estimation ◽  
Aerial Survey ◽  
Regression Method ◽  
Regression Equations ◽  
Regression Analyses ◽  
True Density ◽  
Balanced Design ◽  
Multiple Regression Method

Two experiments examined the accuracy of the multiple regression method for estimating population density. In experiment I , in a balanced design, an observer counted objectsin simulated strip transects. Multiple regression analyses yielded accurate estimates when true density was low, and overestimated density when true density was high. Regression equations calculated at each level of true density varied from linear to quadratic. A simple polynomial model accurately estimated true density. In experiment 2 an aerial survey of sheep showed that estimated density was highly significantly (P <0.001) different from true density. The results suggest that greater use should be made of established criteria for robust estimation of true density in transect studies.

DETERMINANTS OF FINANCIAL LIQUIDITY IN FEED ENTERPRISES

2018 ◽  
Vol XX (6) ◽  
pp. 41-48 ◽  
Author(s):  
Dorota Czerwińska-Kayzer ◽  
Joanna Florek
Keyword(s):  
Multiple Regression ◽  
Regression Method ◽  
Cause And Effect ◽  
Factors Influencing ◽  
Multiple Regression Method ◽  
Main Factors ◽  
Financial Liquidity

The multiple regression method was used to assess the strength and direction of the influence of selected determinants of financial liquidity. The multiple regression method was used to assess the strength and direction of the influence of selected determinants of financial liquidity. The analysis uses two models of cause-and-effect linkage of factors shaping financial liquidity. The presented research showed that the main factors influencing the liquidity were the structure of assets, the ratio of liabilities coverage, rotation of the current liabilities and the ratio of financing revenues with equity.

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