scholarly journals Modely výškových kriviek jedľovo-bukových porastov Východných Karpát / Models of height curves in fir-beech stands of the Eastern Carpathians

2015 ◽  
Vol 61 (2) ◽  
pp. 107-113
Author(s):  
Tomáš Klouček ◽  
Igor Štefančík ◽  
Rudolf Petráš ◽  
Julian Mecko ◽  
Martin Slávik
Keyword(s):  
Regression Models ◽  
Tree Height ◽  
Repeated Measurements ◽  
Linear Regression Models ◽  
Local Conditions ◽  
Actual Knowledge ◽  
Growing Stock ◽  
Eastern Carpathians ◽  
Lesser Curvature ◽  
Limited Scope

Abstract The models of height curves were derived from repeated measurements at six permanent research plots in the experimental object of Komárnik situated in the Eastern Carpathians. During more than 50 years of investigation, the heights of 1,346 beech and 1,208 fir trees were measured. Tree heights had a great variability, but the stage-shift of height curves was not confirmed. The non-linear regression models of height curves for beech and fir were derived, where tree height is a function of tree diameter and model height for a selected diameter class. They are based on the Korf growth curve with three parameters. The models explained 90% and 94% of beech and fir height variability, respectively. The models confirmed the actual knowledge that fir had higher tree height increment than beech especially for trees with greater diameters. The comparison of our models to those developed by other authors showed that the shape of height curves slightly differed. Beech curve was characterised by greater, while fir curve by lesser curvature in comparison with other published models. Our models have only local validity due to the limited scope of experimental data. They can be applied under the local conditions in order to perform valuation and simulation of growing stock development and increments of uneven-aged and multistoried fir-beech stands.

scholarly journals ALS as Tool to Study Preferred Stem Inclination Directions

2020 ◽  
Vol 12 (22) ◽  
pp. 3744
Author(s):  
Sebastian Lamprecht ◽  
Johannes Stoffels ◽  
Thomas Udelhoven
Keyword(s):  
Regression Models ◽  
Linear Models ◽  
Tree Height ◽  
Small Scale ◽  
Deciduous Trees ◽  
Linear Regression Models ◽  
Species Specific ◽  
Trunk Orientation ◽  
Significant Factors ◽  
Dependent Interaction

Although gravitropism forces trees to grow vertically, stems have shown to prefer specific orientations. Apart from wind deforming the tree shape, lateral light can result in prevailing inclination directions. In recent years a species dependent interaction between gravitropism and phototropism, resulting in trunks leaning down-slope, has been confirmed, but a terrestrial investigation of such factors is limited to small scale surveys. ALS offers the opportunity to investigate trees remotely. This study shall clarify whether ALS detected tree trunks can be used to identify prevailing trunk inclinations. In particular, the effect of topography, wind, soil properties and scan direction are investigated empirically using linear regression models. 299.000 significantly inclined stems were investigated. Species-specific prevailing trunk orientations could be observed. About 58% of the inclination and 19% of the orientation could be explained by the linear models, while the tree species, tree height, aspect and slope could be identified as significant factors. The models indicate that deciduous trees tend to lean down-slope, while conifers tend to lean leeward. This study has shown that ALS is suitable to investigate the trunk orientation on larger scales. It provides empirical evidence for the effect of phototropism and wind on the trunk orientation.

scholarly journals Correlation between fibre length characteristics and mechanical properties of Tectona grandis wood

2012 ◽  
Vol 4 (2) ◽  
pp. 258-263
Author(s):  
D. N. Izekor ◽  
J. A. Fuwape
Keyword(s):  
Mechanical Properties ◽  
Correlation Analysis ◽  
Correlation Coefficient ◽  
Regression Models ◽  
Fibre Length ◽  
Tree Height ◽  
Tectona Grandis ◽  
Linear Regression Models ◽  
Similar Class ◽  
The Relationship

This study considered the relationship between fibre length characteristics and mechanical properties of Tectona grandis wood aged 15, 20 and 25-year. Six trees of even aged and similar class diameter were used for the study. Wood samples used for the study were systematically collected from three portions at 10, 50 and 90% of the tree height. The test samples were prepared along the radial positions from the pith to the bark. The relationship between fibre length and mechanical properties were examined using linear regression models and correlation coefficient. The results obtained from the correlation analysis carried out to examine the linear relationship between fibre length and mechanical properties of T. grandis wood were 0.924, 0.929 and 0.940 for MOR, MOE and CS parallel to grain. The relationship was highly significant (p < 0.05). Also the correlation coefficient (r) between fibre length and mechanical properties of T. grandis wood were highly significant (p < 0.001). Therefore, fibre length characteristics can be used as an index in predicting the mechanical properties of T. grandis wood.

Optimal Designs in Random Coefficient Linear Regression Models

1996 ◽  
Vol 46 (3-4) ◽  
pp. 211-230 ◽  
Author(s):  
Erkki P. Liski ◽  
Arto Luoma ◽  
Bikas K. Sinha
Keyword(s):  
Parameter Estimation ◽  
Linear Regression ◽  
Upper Bound ◽  
Regression Models ◽  
Random Coefficients ◽  
Repeated Measurements ◽  
Optimal Designs ◽  
Slope Parameter ◽  
Linear Regression Models ◽  
Estimation And Prediction

In this paper we consider a random coefficients regression model in the context of repeated measurements. The measurements are taken at consecutive points for several experimental units, and the total number of measurements have a fixed upper bound. Observations on the same unit at different points will be correlated while observations on two differents units are uncorrelated. We present optimal designs for slope parameter estimation and prediction.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

scholarly journals Relationships between test positivity rate, total laboratory confirmed cases of malaria, and malaria incidence in high burden settings of Uganda: an ecological analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Jaffer Okiring ◽  
Adrienne Epstein ◽  
Jane F. Namuganga ◽  
Victor Kamya ◽  
Asadu Sserwanga ◽  
...  
Keyword(s):  
Regression Models ◽  
Malaria Incidence ◽  
Temporal Changes ◽  
Linear Regression Models ◽  
High Burden ◽  
Exponential Regression ◽  
Malaria Morbidity ◽  
Laboratory Test Results ◽  
Combining Data ◽  
Catchment Areas

Abstract Background Malaria surveillance is critical for monitoring changes in malaria morbidity over time. National Malaria Control Programmes often rely on surrogate measures of malaria incidence, including the test positivity rate (TPR) and total laboratory confirmed cases of malaria (TCM), to monitor trends in malaria morbidity. However, there are limited data on the accuracy of TPR and TCM for predicting temporal changes in malaria incidence, especially in high burden settings. Methods This study leveraged data from 5 malaria reference centres (MRCs) located in high burden settings over a 15-month period from November 2018 through January 2020 as part of an enhanced health facility-based surveillance system established in Uganda. Individual level data were collected from all outpatients including demographics, laboratory test results, and village of residence. Estimates of malaria incidence were derived from catchment areas around the MRCs. Temporal relationships between monthly aggregate measures of TPR and TCM relative to estimates of malaria incidence were examined using linear and exponential regression models. Results A total of 149,739 outpatient visits to the 5 MRCs were recorded. Overall, malaria was suspected in 73.4% of visits, 99.1% of patients with suspected malaria received a diagnostic test, and 69.7% of those tested for malaria were positive. Temporal correlations between monthly measures of TPR and malaria incidence using linear and exponential regression models were relatively poor, with small changes in TPR frequently associated with large changes in malaria incidence. Linear regression models of temporal changes in TCM provided the most parsimonious and accurate predictor of changes in malaria incidence, with adjusted R2 values ranging from 0.81 to 0.98 across the 5 MRCs. However, the slope of the regression lines indicating the change in malaria incidence per unit change in TCM varied from 0.57 to 2.13 across the 5 MRCs, and when combining data across all 5 sites, the R2 value reduced to 0.38. Conclusions In high malaria burden areas of Uganda, site-specific temporal changes in TCM had a strong linear relationship with malaria incidence and were a more useful metric than TPR. However, caution should be taken when comparing changes in TCM across sites.

Sign in / Sign up

Export Citation Format

Share Document