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 Hand Hygiene Knowledge and Self-Reported Hand Washing Behaviors among Restaurant Kitchen Chefs in Jiangsu Province, China

2021 ◽  
Vol 18 (4) ◽  
pp. 2149
Author(s):  
Bin Cui ◽  
Shao Ying Li ◽  
Linda Dong-Ling Wang ◽  
Xiang Chen ◽  
Jun Ke ◽  
...  
Keyword(s):  
Hand Hygiene ◽  
Regression Models ◽  
Restaurant Industry ◽  
Jiangsu Province ◽  
Hand Washing ◽  
Small Scale ◽  
Linear Regression Models ◽  
Foodborne Illnesses ◽  
Close Attention ◽  
Chi Square

Inadequate hand washing among chefs is a major contributor to outbreaks of foodborne illnesses originating in restaurants. Although many studies have evaluated hand hygiene knowledge (HHK) and self-reported hand washing behaviors (HWBs) in restaurant workers in different countries, little is known about HHK and HWBs in restaurant kitchen chefs, particularly in China. In this study, we interviewed 453 restaurant kitchen chefs in Jiangsu Province in China regarding their HHK and HWBs and used Chi-square tests (Fisher exact tests), pairwise comparisons, and linear regression models to analyze the responses and identify determinants of HHK and HWBs. Results reveal that less frequent hand washing after leaving work temporarily and after touching used cutlery were the main issues among restaurant kitchen chefs in Jiangsu Province. Kitchen hands had lower levels of HHK and engaged less frequently in good HWBs than the other type of chefs. Furthermore, working in a large restaurant and having worked in the restaurant industry for a longer amount of time were correlated with better HHK and HWBs. These findings suggest that close attention should be paid to the HWBs of chefs during food preparation, that kitchen hands are the key group of restaurant kitchen workers who need training in HHK, and that regulatory activities should focus on small-scale restaurants.

scholarly journals Robust Statistical Inference in Generalized Linear Models Based on Minimum Renyi’s Pseudodistance Estimators

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 123
Author(s):  
María Jaenada ◽  
Leandro Pardo
Keyword(s):  
Generalized Linear Models ◽  
Influence Function ◽  
Regression Models ◽  
Linear Models ◽  
Asymptotic Properties ◽  
Significant Loss ◽  
Superior Performance ◽  
Test Statistics ◽  
Linear Regression Models ◽  
Type Test

Minimum Renyi’s pseudodistance estimators (MRPEs) enjoy good robustness properties without a significant loss of efficiency in general statistical models, and, in particular, for linear regression models (LRMs). In this line, Castilla et al. considered robust Wald-type test statistics in LRMs based on these MRPEs. In this paper, we extend the theory of MRPEs to Generalized Linear Models (GLMs) using independent and nonidentically distributed observations (INIDO). We derive asymptotic properties of the proposed estimators and analyze their influence function to asses their robustness properties. Additionally, we define robust Wald-type test statistics for testing linear hypothesis and theoretically study their asymptotic distribution, as well as their influence function. The performance of the proposed MRPEs and Wald-type test statistics are empirically examined for the Poisson Regression models through a simulation study, focusing on their robustness properties. We finally test the proposed methods in a real dataset related to the treatment of epilepsy, illustrating the superior performance of the robust MRPEs as well as Wald-type tests.

scholarly journals Regression models for estimating chick hatchling weight from some egg geometry traits

2018 ◽  
Vol 34 (3) ◽  
pp. 323-334
Author(s):  
Nadya Mincheva ◽  
Mitko Lalev ◽  
Magdalena Oblakova ◽  
Pavlina Hristakieva
Keyword(s):  
Linear Regression ◽  
Surface Area ◽  
Regression Models ◽  
Linear Models ◽  
Geometric Mean ◽  
Coefficient Of Determination ◽  
Regression Equations ◽  
Linear Regression Models ◽  
Egg Weight ◽  
Mean Diameter

The prediction of chicks? weight before hatching is an important element of selection, aimed at improving the uniformity rate and productivity of birds. With this regards, our goal was to develop and evaluate optimum models for similar prediction in two White Plymouth Rock chickens lines - line L and line K on the basis of the incubation egg weight and egg geometry characteristics - egg maximum breadth (B), egg length (L), geometric mean diameter (Dg), egg volume (V), egg surface area (S). A total of 280 eggs (140 from each line) laid by 40-weekold hens were randomly selected. Mean arithmetic values, standard deviations and coefficients of variation of studied parameters were determined for each line. Correlation coefficients between the weight of hatchlings and predictors were the highest for egg weight, geometric mean diameter, volume and surface area of eggs (r=0.731-0.779 for line L; r=0.802-0.819 for line ?). Nine linear regression models were developed and their accuracy evaluated. The regression equations of hatchlings? weight vs egg length had the lowest coefficient of determination (0.175 for line K and 0.291 for line L), but when egg length and breadth entered the model together, its value increased significantly up to 0.541 and 0.665 for lines L and K, respectively. The weight of day-old chicks from line L could be predicted with higher accuracy with a model involving egg surface area apart egg weight (ChW=0.513EW+0.282S - 10.345; R2=0.620). In line ? a more accurate prognosis was attained by adding egg breadth as an additional predictor to the weight in the model (ChW=0.587EW+0.566? - 19.853; R2=0.692). The study demonstrated that multiple linear regression models were more precise that single linear models.

scholarly journals Innovation of price adjustment mechanisms to support investment in solar power in Germany

2018 ◽  
Vol 64 ◽  
pp. 02007 ◽  
Author(s):  
Thi Hiep Do ◽  
Hoffmann Clemens
Keyword(s):  
Regression Models ◽  
Feedback System ◽  
Feedback Mechanism ◽  
Vital Role ◽  
Price Adjustment ◽  
Small Scale ◽  
Linear Regression Models ◽  
Pv System ◽  
Adjustment Mechanism ◽  
Adjustment Mechanisms

It has been widely agreed that to incentivize renewables integration into the power system, not only pricing mechanisms, but price adjustment mechanisms have played a vital role, and it has been true for the German Energiewende. This study is to carry out a detailed analysis of investment results influenced by innovative price adjustment mechanisms from an auto degression rate to a feedback system. Employing linear regression models for the historical data of investment in small-scale rooftop PV projects in Germany, we have found out a better correlation between PV system price and feed-in tariff (92.09%) under quarter feedback and monthly adjustment mechanism compared to an annual feedback system. However, the underinvestment in recent years reveals that a feedback mechanism without specific mathematical shapes was not effective enough in term of meeting the targeted volume. Therefore, further researches are to design mathematical images of feedback mechanism in order to find out the trajectory of electricity price in the future which at the same time satisfies the target of investment and economic effectiveness.

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 Studi Teknik Tradisional Budidaya dan Produksi Kenanga Jawa (Cananga odorata f. macrophylla) di Blitar

2020 ◽  
Vol 11 (3) ◽  
pp. 177-182
Author(s):  
Hariadi Propantoko ◽  
Irdika Mansur ◽  
Arum Sekar Wulandari
Keyword(s):  
Essential Oil ◽  
Tree Height ◽  
Tree Canopy ◽  
Tree Age ◽  
Small Scale ◽  
Factors Affecting ◽  
Flower Production ◽  
Total Tree ◽  
Cananga Odorata ◽  
Significant Factors

Java kenanga or kenanga (Cananga odorata f. macrophylla) is a tropical and sub-tropical tree species that grows naturally in Indonesia and produces essential oil. This species has been cultivated in the past by community in Indonesia, mainly on their yard. The population of kenanga has decreased significantly, but in Blitar district the community is still doing cultivating the species although in a small scale. The purpose of this research is to observe the cultivation efforts by the community and also kenanga flower production in Blitar district. This research was conducted by interviewing farmers and observation of kenanga trees in the field. The results showed that cultivation efforts being made to improve the production of kenanga flower is by pruning, fertilizing, flowering routine and retrieval or emoval of kenanga fruit. The average kananga flower production reached 381 kg / year / tree in the age group above 11 years. Factors that affect flower production were tree age (years), total tree height (m), diameter at breast height (cm) and the width tree canopy (m2). The most significant factors affecting flower production were tree diameter and width of tree canopy. Cultivation efforts being made to improve the production of kenanga flower is by pruning, fertilizing, flowering routine and retrieval or removal of kenanga fruit. Keywords: Cananga odorata f. macrophylla, essential oil, cultivation, Blitar

scholarly journals Valuation of Large Variable Annuity Portfolios Using Linear Models with Interactions

2018 ◽  
Author(s):  
Guojun Gan
Keyword(s):  
Linear Regression ◽  
Life Insurance ◽  
Predictive Models ◽  
Regression Models ◽  
Linear Models ◽  
Insurance Companies ◽  
Linear Regression Models ◽  
Insurance Product ◽  
Valuation Process ◽  
Speed Up

A variable annuity is a popular life insurance product that comes with financial guarantees. Using Monte Carlo simulation to value a large variable annuity portfolio is extremely time-consuming. Metamodeling approaches have been proposed in the literature to speed up the valuation process. In metamodeling, a metamodel is first fitted to a small number of variable annuity contracts and then used to predict the values of all other contracts. However, metamodels that have been investigated in the literature are sophisticated predictive models. In this paper, we investigate the use of linear regression models with interaction effects for the valuation of large variable annuity portfolios. Our numerical results show that linear regression models with interactions are able to produce accurate predictions and can be useful additions to the toolbox of metamodels that insurance companies can use to speed up the valuation of large VA portfolios.

scholarly journals Valuation of Large Variable Annuity Portfolios Using Linear Models with Interactions

Risks ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 71 ◽  
Author(s):  
Guojun Gan
Keyword(s):  
Linear Regression ◽  
Life Insurance ◽  
Predictive Models ◽  
Regression Models ◽  
Linear Models ◽  
Insurance Companies ◽  
Linear Regression Models ◽  
Insurance Product ◽  
Valuation Process ◽  
Speed Up

A variable annuity is a popular life insurance product that comes with financial guarantees. Using Monte Carlo simulation to value a large variable annuity portfolio is extremely time-consuming. Metamodeling approaches have been proposed in the literature to speed up the valuation process. In metamodeling, a metamodel is first fitted to a small number of variable annuity contracts and then used to predict the values of all other contracts. However, metamodels that have been investigated in the literature are sophisticated predictive models. In this paper, we investigate the use of linear regression models with interaction effects for the valuation of large variable annuity portfolios. Our numerical results show that linear regression models with interactions are able to produce accurate predictions and can be useful additions to the toolbox of metamodels that insurance companies can use to speed up the valuation of large VA portfolios.

scholarly journals Estimation of Causal Functional Linear Regression Models

2017 ◽  
Vol 9 (6) ◽  
pp. 106
Author(s):  
J.C.S. De Miranda
Keyword(s):  
Linear Regression ◽  
Tensor Product ◽  
Linear Regression Model ◽  
Regression Models ◽  
Linear Models ◽  
Linear Regression Models ◽  
Functional Responses ◽  
Functional Linear Models ◽  
Triangular Region ◽  
Functional Linear Regression

We present a methodology for estimating causal functional linear models using orthonormal tensor product expansions. More precisely, we estimate the functional parameters $\alpha$ and $\beta$ that appear in the causal functional linear regression model:$$\mathcal{Y}(s)=\alpha(s)+\int_a^b\beta(s,t)\mathcal{X}(t)\mathrm{d}t+\mathcal{E}(s),$$ where  $\mbox{supp } \beta \subset \mathfrak{T},$ and $\mathfrak{T}$ is the closed triangular region whose vertexes are $(a,a) , (b,a)$ and $(b,b).$ We assume we have an independent sample $\{ (\mathcal{Y}_k,\mathcal{X}_k) : 1\le k \le N, k\in \mathbb{N}\}$ of observations where the $\mathcal{X}_k $'s are functional covariates, the $\mathcal{Y}_k$'s are time order preserving functional responses and $\mathcal{E}_k,$ $1\le k \le N,$ is i.i.d. zero mean functional noise.

scholarly journals METHODS OF THE ESTIMATED TWO-PARAMETER LINEAR REGRESSION MODELSFOR DIAGNOSIS OF BRONCHIAL ASTHMA SEVERITY IN CHILDREN

2021 ◽  
pp. 23-30
Author(s):  
PIHNASTYI OLEH MYKHAILOVYCH ◽  
KOZHYNA OLGA SERGEYEVNA
Keyword(s):  
Linear Regression ◽  
Bronchial Asthma ◽  
Regression Models ◽  
Linear Models ◽  
Asthma Severity ◽  
Linear Regression Models ◽  
Experimental Data Processing ◽  
Preliminary Experimental Data ◽  
Factor Regression ◽  
Two Parameter

Objectives: Prognostication of bronchial asthma severity in children by means of two-parameter regression models building. Methods: A clinical study of 70 children with bronchial asthma diagnosis of 6 to 18 years old was done.142 factors were analyzed and a degree of relationship among them was revealed. Single-factor regression models were used during preliminary experimental data processing. Results: The correlation connection between the value observed and the factors under research was revealed. The method of two-parameter linear models with a fair accuracy was developed. Conclusion: The suggested method of approximate two-parameter linear regression models can be used for preliminary analysis of medical research data where the value observed depends on a big number of loosely connected factors.

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