scholarly journals Risk factors influencing the probability of browsing by hoofed game on forest trees

2008 ◽  
Vol 53 (No. 8) ◽  
pp. 359-363 ◽  
Author(s):  
V. Malík ◽  
J. Stuchlý
Keyword(s):  
Risk Factors ◽  
Tree Species ◽  
Logit Model ◽  
Least Squares Method ◽  
Chemical Elements ◽  
Ordinary Least Squares ◽  
Likelihood Method ◽  
Forest Trees ◽  
Scotch Pine ◽  
Factors Influencing

In this paper we analyze how selected risk factors determine the probability of browsing by hoofed game on forest trees. Risk factors covered by the model are: tree species (Norway spruce or Scotch pine), time period (season: spring + summer or autumn + winter) and chemical structure of bark (content of selected nutrients and chemical elements). We use a logit model for these purposes. We formulate the model and perform linear transformation by the natural log. Since the disturbance term in the logit model is heteroscedastic, we cannot use the ordinary least-squares method to estimate the parameters of the model. In this case the maximum likelihood method included in STATGRAPHICS Plus for Windows program is used for its estimation. We use a random sample of data including 59 trees. We do the interpretations of the estimated parameters and other characteristics. We demonstrate how the estimated probabilities depend on the considered factor. The model explains 44.1% of variations of the logits, the model is statistically significant. All regression coefficients are significant at least at 12% confidence level. Among the main explanatory variables (content of P, Ca, NO<sub>3</sub>, tree species and season), the P and Ca contents in the bark of the tree are the most important factors influencing the probability of future damage to the tree.

scholarly journals A practical procedure for estimation of linear models via asymptotic quasi-likelihood

1999 ◽  
Vol 3 (1) ◽  
pp. 21-39 ◽  
Author(s):  
Riccardo Biondini ◽  
Yan-Xia Lin ◽  
Sifa Mvoi
Keyword(s):  
Linear Models ◽  
Least Squares Method ◽  
Ordinary Least Squares ◽  
Likelihood Method ◽  
Unknown Parameters ◽  
Predictable Process ◽  
Practical Procedure ◽  
Finite Dimensional ◽  
Dimensional Distribution ◽  
Ordinary Least Squares Method

This paper is concerned with the application of an asymptotic quasi-likelihood practical procedure to estimate the unknown parameters in linear stochastic models of the form yt=ft(θ)+Mt(θ)(t=1,2,..,T) , where ft is a linear predictable process of θ and Mt is an error term such that E(Mt|Ft−1)=0 and E(Mt2|Ft−1)<∞ and F is a σ-field generated from{ys}s≤t . For this model, to estimate the parameter θ∈Θ, the ordinary least squares method is usually inappropriate (if there is only one observable path of {yt} and if E(Mt2|Ft−1) is not a constant) and the maximum likelihood method either does not exist or is mathematically intractable. If the finite dimensional distribution of Mt is unknown, to obtain a good estimate of θ an appropriate predictable process gt should be determined. In this paper, criteria for determining gt are introduced which, if satisfied, provide more accurate estimates of the parameters via the asymptotic quasi-likelihood method.

scholarly journals Bayesian and Classical Estimation for the One Parameter Double Lindley Model

2020 ◽  
pp. 409-420 ◽  
Author(s):  
Mohamed Ibrahim ◽  
Wahhab Mohammed ◽  
Haitham M. Yousof
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Estimation Method ◽  
Ordinary Least Squares ◽  
Likelihood Method ◽  
Unknown Parameters ◽  
Weighted Least Squares Method ◽  
Von Mises ◽  
New Distribution

The main motivation of this paper is to show how the different frequentist estimators of the new distribution perform for different sample sizes and different parameter values and to raise a guideline in choosing the best estimation method for the new model. The unknown parameters of the new distribution are estimated using the maximum likelihood method, ordinary least squares method, weighted least squares method, Cramer-Von-Mises method and Bayesian method. The obtained estimators are compared using Markov Chain Monte Carlo simulations and we observed that Bayesian estimators are more efficient compared to other the estimators.

Risk factors influencing the prognosis in patients with arterial hypertension

HYPERTENSION ◽  
2018 ◽  
Vol 0 (2.58) ◽  
pp. 59-69
Author(s):  
Yu.M. Sirenko ◽  
G.D. Radchenko ◽  
O.L. Rekovets
Keyword(s):  
Risk Factors ◽  
Arterial Hypertension ◽  
Factors Influencing

Prevalence of obesity and its risk factors among school children in Karachi, Pakistan

2018 ◽  
Vol 48 (4) ◽  
pp. 266-269 ◽  
Author(s):  
Naveed Mansoori ◽  
Nighat Nisar ◽  
Naveen Shahid ◽  
Syed Muhammad Mubeen ◽  
Shahid Ahsan
Keyword(s):  
Risk Factors ◽  
School Children ◽  
Dietary Habits ◽  
Overweight And Obesity ◽  
Growth Chart ◽  
Sociodemographic Characteristics ◽  
Cross Sectional ◽  
Factors Influencing ◽  
Private And Public ◽  
Prevalence Of Obesity

A cross-sectional questionnaire study was conducted during 2012 in private and public-sector schools of Karachi to determine the prevalence and factors influencing overweight and obesity among school children (aged 11–15 years). Sociodemographic characteristics and dietary habits were explored. The CDC Growth Chart was used to record height and weight. Of a total of 887 children, being overweight and frankly obese was found in 169 (19.1%) and 96 (10.8%), respectively. Of these, 176 (66.4%) were from private schools, and significant associations were found in 202 (76.2%) who were spending > 2 h/day watching television and 139 (52.5%) sleeping > 8 h/day.

scholarly journals Influence of Fiscal Policies and Labor Market Characteristics on Sustainable Social Insurance Budgets—Empirical Evidence from Central and Eastern European Countries

2021 ◽  
Vol 13 (11) ◽  
pp. 6197
Author(s):  
Adriana Florina Popa ◽  
Stefania Amalia Jimon ◽  
Delia David ◽  
Daniela Nicoleta Sahlian
Keyword(s):  
Labor Market ◽  
Social Insurance ◽  
Social Protection ◽  
Least Squares Method ◽  
Panel Study ◽  
Ordinary Least Squares ◽  
Political Agenda ◽  
Fiscal Policies ◽  
Protection Systems ◽  
Social Protection Systems

Social protection systems are a key factor for ensuring the long-term sustainability and stability of economies in the European Union, their reform being nowadays present in the political agenda of member states. Aging and the dependence on mandatory levies applied to the employed population on the labor market represent a threat for the sustainability of public social protection systems. In terms of sustainability, our purpose was to highlight the factors influencing social insurance budgets, considering the fiscal policies implemented in six countries of Central and Eastern Europe and their particular labor market characteristics. Therefore, a panel study based on a regression model using the Ordinary Least Squares method (OLS) with cross section random effects was used to determine the correlations between funding sources and labor market specific indicators. The data analyzed led to relevant results that emphasize the dependence of social insurance budgets on positive factors such as the average level of salaries, the share of compulsory social contributions, the unemployment rate, and the human development index, suggesting the continuing need for professional and personal development of the workforce.

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