Development, validation, and application of a model of intra- and inter-tree variability of wood density for lodgepole pine in western Canada

2013 ◽  
Vol 43 (12) ◽  
pp. 1172-1180 ◽  
Author(s):  
Mingkai Peng ◽  
James D. Stewart
Keyword(s):  
Random Effects ◽  
Wood Density ◽  
Fixed Effects ◽  
Lodgepole Pine ◽  
Wood Quality ◽  
Random Effect ◽  
Ring Width ◽  
Tree Level ◽  
Stochastic Variation ◽  
Data Set

Wood density is an important characteristic for evaluating wood quality and estimating tree biomass. The ring-level focus of most density models requires inputs and produces predictions at a scale at which industry does not currently operate. Our objective was to develop a model at a scale intermediate between ring and tree levels that would capture the significant, operationally relevant variability that exists within lodgepole pine (Pinus contorta Douglas ex Loudon) trees. We developed a model for estimating mean wood density for groups of five growth rings using a nonlinear mixed-effects modelling approach. The data were collected from six long-term silviculture research trials in Alberta and British Columbia, Canada. An independent data set from west-central Alberta was used for validation. Our results indicated that the density variation pattern can be reproduced using ring width and distance from pith as fixed effects and including site- and tree-level attributes as random effects. The stochastic variation of density among trees was large. Based on the estimated tree-level random effect distribution, prediction bands conditional on simulated random effects were proposed to assess intertree variability of density within a site. Estimation of site-level random effects may reduce bias for sites with low or high wood density.

scholarly journals A random effects population dynamics model based on proportions-at-age and removal data for estimating total mortality

2012 ◽  
Vol 69 (11) ◽  
pp. 1881-1893 ◽  
Author(s):  
Verena M. Trenkel ◽  
Mark V. Bravington ◽  
Pascal Lorance
Keyword(s):  
Population Dynamics ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Total Mortality ◽  
Estimation Bias ◽  
Effective Sample Size ◽  
Dynamics Model ◽  
Population Dynamics Model ◽  
Study Parameter

Catch curves are widely used to estimate total mortality for exploited marine populations. The usual population dynamics model assumes constant recruitment across years and constant total mortality. We extend this to include annual recruitment and annual total mortality. Recruitment is treated as an uncorrelated random effect, while total mortality is modelled by a random walk. Data requirements are minimal as only proportions-at-age and total catches are needed. We obtain the effective sample size for aggregated proportion-at-age data based on fitting Dirichlet-multinomial distributions to the raw sampling data. Parameter estimation is carried out by approximate likelihood. We use simulations to study parameter estimability and estimation bias of four model versions, including models treating mortality as fixed effects and misspecified models. All model versions were, in general, estimable, though for certain parameter values or replicate runs they were not. Relative estimation bias of final year total mortalities and depletion rates were lower for the proposed random effects model compared with the fixed effects version for total mortality. The model is demonstrated for the case of blue ling (Molva dypterygia) to the west of the British Isles for the period 1988 to 2011.

scholarly journals The Impact of Misspecified Random Effect Distribution in a Weibull Regression Mixed Model

Stats ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 48-76
Author(s):  
Freddy Hernández ◽  
Viviana Giampaoli
Keyword(s):  
Weibull Distribution ◽  
Random Effects ◽  
Mixed Models ◽  
Fixed Effects ◽  
Mixed Model ◽  
Random Effect ◽  
Estimation Procedure ◽  
Weibull Regression ◽  
Two Parameters ◽  
The Impact

Mixed models are useful tools for analyzing clustered and longitudinal data. These models assume that random effects are normally distributed. However, this may be unrealistic or restrictive when representing information of the data. Several papers have been published to quantify the impacts of misspecification of the shape of the random effects in mixed models. Notably, these studies primarily concentrated their efforts on models with response variables that have normal, logistic and Poisson distributions, and the results were not conclusive. As such, we investigated the misspecification of the shape of the random effects in a Weibull regression mixed model with random intercepts in the two parameters of the Weibull distribution. Through an extensive simulation study considering six random effect distributions and assuming normality for the random effects in the estimation procedure, we found an impact of misspecification on the estimations of the fixed effects associated with the second parameter σ of the Weibull distribution. Additionally, the variance components of the model were also affected by the misspecification.

Influence of Growth Rate and Cambial Age on Density of Rauli (Nothofagus nervosa) in Relation to Vessel Lumen Areas and Numbers

Holzforschung ◽  
1999 ◽  
Vol 53 (2) ◽  
pp. 199-203 ◽  
Author(s):  
M. P. Denne ◽  
C. M. Cahalan ◽  
D. P. Aebischer
Keyword(s):  
Growth Rate ◽  
Wood Density ◽  
Wood Quality ◽  
Ring Width ◽  
Substantial Effect ◽  
Present Sample ◽  
Vessel Lumen ◽  
Cambial Age ◽  
Old Trees ◽  
Nothofagus Nervosa

Summary To assess the likely effects of silvicultural treatment on the wood quality of Nothofagus nervosa grown in the UK, and the possibilities of independent selection within seed origins for density and growth rate, ring width and wood density were analysed from pith to bark of 19 trees. Variations in vessel lumen size, vessel number mm−2, and total lumen area mm−2 were analysed in ten trees. Since density increased by only 0.005g cm−3 per mm increase in ring width, silvicultural practices such as initial spacing and thinning are not likely to have a substantial effect on the wood density of rauli. Similarly, variation in density with cambial age was significant but relatively minor in the 40- and 60-year old trees of the present sample, suggesting that the rotation length is unlikely to have any practical influence on the density of rauli. Considerable between-tree differences in density were found which did not correspond to differences in ring width, suggesting it should be feasible to select independently for density and growth rate. These differences in density were associated with differences in both vessel lumen size and vessel number mm−2

Influence of feeding damage by small mammals on tree growth and wood quality in young lodgepole pine

1993 ◽  
Vol 23 (5) ◽  
pp. 799-809 ◽  
Author(s):  
Thomas P. Sullivan ◽  
Harry Coates ◽  
Les A. Jozsa ◽  
Paul K. Diggle
Keyword(s):  
Lodgepole Pine ◽  
Wood Quality ◽  
Ring Width ◽  
Small Diameter ◽  
Height Growth ◽  
Diameter Increment ◽  
Significant Difference ◽  
Small Diameter Trees ◽  
Severe Degree ◽  
The Impact

This study assessed the impact of feeding injuries by snowshoe hare (Lepusamericanus Erxleben) and red squirrel (Tamiasciurushudsonicus Erxleben) on diameter growth, height growth, and wood quality of juvenile lodgepole pine (Pinuscontorta Dougl. var latifolia Engelm.) at Prince George and in the Cariboo Region, British Columbia. In the Prince George control stand, severe girdling damage (50–99% stem circumference) suppressed diameter and height growth of small-diameter (4.1–6.0 cm) trees, but had no effect on larger stems (6.1–8.0 cm). In the spaced stand, diameter and height increments also declined significantly with degree of partial girdling, particularly in small-diameter (3.1–5.0 cm) trees. Paradoxically, diameter increment increased significantly with degree of partial girdling in both stands at the Cariboo study area. Presumably squirrels prefer to feed on vigorous stems, and the lost growth of these trees may be substantial. There was no significant difference in amount of compression wood nor total solvent and water extractives between undamaged and damaged trees. Fiber lengths in wound-associated wood were consistently 19–21% lower than in controls. Damaged trees had greater average ring width and density than undamaged trees. The average increase in relative density of damaged over undamaged trees was 0.0343. These results suggest that a severe degree of partial girdling (which likely occurs more often in small-diameter trees) may significantly affect growth of lodgepole pine, particularly small (<5.0 cm DBH) trees.

Determinants of SME growth

2016 ◽  
Vol 39 (9) ◽  
pp. 966-986 ◽  
Author(s):  
Habib Kachlami ◽  
Darush Yazdanfar
Keyword(s):  
Random Effects ◽  
Financial Institutions ◽  
Significant Influence ◽  
Fixed Effects ◽  
Explanatory Power ◽  
Ordinary Least Squares ◽  
Firm Level ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to study the firm-level financial variables affecting the growth of small and medium-sized enterprises (SMEs). Design/methodology/approach The study applies a resource-based view to analyze the firm-level as well as industry-level determinants of SME growth. Empirical evidence has also been provided from a data set of SMEs in Sweden to support the hypotheses. For a robust statistical analysis, three models – ordinary least squares (OLS) regression, random-effects regression and fixed-effects regression – are used to examine the influence of explanatory variables on growth. Findings The findings of this study show a positive and significant influence of profitability, short-term debt and size on a firm’s growth across all three models. Results regarding the influence of long-term debt on growth, however, are mixed. While the results of a fixed-effect model show the negative and significant influence of long-term debt on growth, the results according to OLS and random effects show long-term debt positively related to growth. Research limitations/implications This study has been conducted over a period of four years and in the context of Sweden which may limit the generalizability of its results for longer periods and for different contexts. Moreover, the low explanatory power of the models implies the need to also consider other types of variables, such as managerial or socio-economic variables, to better explain the determinants of SME growth. Practical implications Understanding the determinants of growth can be important for policy makers, SME managers and financial institutions. The findings of this study can be used for designing policies which stimulate SME growth. Realizing the financial resources that influence growth can also help SME managers and financial institutions to understand each other’s need for better cooperation. Originality/value This paper applies different models for analyzing large and cross-sectoral data regarding SME growth in the context of Sweden.

scholarly journals Impact of Full IFRS, Accounting Standards for SMES and Company Demographics on Firms’ Return on Asset and Return on Equity using Panel Data Regression

2019 ◽  
Vol 8 (6S) ◽  
pp. 589-601 ◽  
Keyword(s):  
Least Squares ◽  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Ordinary Least Squares ◽  
Lagrangian Multiplier ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Real Property ◽  
The Impact

Due to globalization, markets are becoming more interconnected as the companies are engaged in doing cross-border offerings. Currently, competitions are intensified because Domestic organizations discover themselves competing with each nearby opposite numbers and worldwide companies. But one component that hinders SMEs is the need for reliable and similar monetary data. According to Abarca (2014), adoption of a high-quality and consistent set of accounting requirements is critical so as for the businesses to remain competitive in ASEAN member states. This paper ambitions to answer the query, what modified into the extent of the impact of compliance with full IFRS and IFRS for SMEs on profitability of agencies belong to real property enterprise? This paper moreover sought to decide whether there may be a sizeable distinction among the groups’ compliance with the overall PFRS and the PFRS for SMEs and to determine whether or now not there is a massive distinction among the companies’ financial normal overall performance earlier than and after the adoption of the PFRS for SMEs.Paired T-test have become employed in case you need to determine whether there is a big distinction between the agencies’ compliance with the entire PFRS and the PFRS for SMEs and to decide whether or not there may be a big difference some of the groups’ monetary performance earlier than and after the adoption of the PFRS for SMEs. Using STATA, the great appropriate version for every economic ratio on the subject of degree of compliance emerge as determined on. First, take a look at parm command became used to find out which most of the Least Squares Dummy Variable Regression Modes (LSDV1, LSDV2, LSDV3) underneath the Fixed Effects Model is the ideal version. Afterwards, Hausman Fixed Random Test changed into used to pick out out which is more suitable amongst Fixed Effects Model and Random Effects Model. If Fixed Effects Model modified into the more appropriate one, the Wald’s test turn out to be used to determine the best version among Fixed Effects Model and Ordinary Least Squares Model. On the alternative hand, if Random Effects Model became the more suitable one, the Breusch and Pagan Lagrangian Multiplier Test for Random Effect have become used to decide the satisfactory version amongst Random Effects Model and Ordinary Least Squares. Moreover, if Ordinary Least Squares became the splendid model, it is going to be in addition tested to check for heteroscedasticity and multicollinearity. White’s test became used to check for heterescedasticity and Variance Inflation Factor have become used to test if multicollinearity is gift. The results display that the adoption of PFRS for SMEs stepped forward the compliance of Philippine real property SMEs. However, no vast alternate became said inside the financial average performance of those companies (as measured with the resource of cross back on assets and go back on equity). This was further supported by the results of the panel regression. This means that despite having a relatively

scholarly journals The Impact of Ignoring a Crossed Factor in Cross-Classified Multilevel Modeling

2021 ◽  
Vol 12 ◽  
Author(s):  
Soyoung Kim ◽  
Yoonhwa Jeong ◽  
Sehee Hong
Keyword(s):  
Random Effects ◽  
Hierarchical Linear Modeling ◽  
Fixed Effects ◽  
Random Effect ◽  
Information Criteria ◽  
Linear Modeling ◽  
Random Effect Modeling ◽  
Error Bias ◽  
The Impact ◽  
Level 2

The present study investigated estimate biases in cross-classified random effect modeling (CCREM) and hierarchical linear modeling (HLM) when ignoring a crossed factor in CCREM considering the impact of the feeder and the magnitude of coefficients. There were six simulation factors: the magnitude of coefficient, the correlation between the level 2 residuals, the number of groups, the average number of individuals sampled from each group, the intra-unit correlation coefficient, and the number of feeders. The targeted interests of the coefficients were four fixed effects and two random effects. The results showed that ignoring a crossed factor in cross-classified data causes a parameter bias for the random effects of level 2 predictors and a standard error bias for the fixed effects of intercepts, level 1 predictors, and level 2 predictors. Bayesian information criteria generally outperformed Akaike information criteria in detecting the correct model.

scholarly journals Including random effects in statistical models in ecology: fewer than five levels?

2021 ◽  
Author(s):  
Dylan G.E. Gomes
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Linear Models ◽  
Random Effect ◽  
Mixed Effects ◽  
Parameter Estimates ◽  
Type I ◽  
Type I Errors ◽  
Ecological Sites ◽  
Generalized Linear Mixed Effects

AbstractAs generalized linear mixed-effects models (GLMMs) have become a widespread tool in ecology, the need to guide the use of such tools is increasingly important. One common guideline is that one needs at least five levels of a random effect. Having such few levels makes the estimation of the variance of random effects terms (such as ecological sites, individuals, or populations) difficult, but it need not muddy one’s ability to estimate fixed effects terms – which are often of primary interest in ecology. Here, I simulate ecological datasets and fit simple models and show that having too few random effects terms does not influence the parameter estimates or uncertainty around those estimates for fixed effects terms. Thus, it should be acceptable to use fewer levels of random effects if one is not interested in making inference about the random effects terms (i.e. they are ‘nuisance’ parameters used to group non-independent data). I also use simulations to assess the potential for pseudoreplication in (generalized) linear models (LMs), when random effects are explicitly ignored and find that LMs do not show increased type-I errors compared to their mixed-effects model counterparts. Instead, LM uncertainty (and p values) appears to be more conservative in an analysis with a real ecological dataset presented here. These results challenge the view that it is never appropriate to model random effects terms with fewer than five levels – specifically when inference is not being made for the random effects, but suggest that in simple cases LMs might be robust to ignored random effects terms. Given the widespread accessibility of GLMMs in ecology and evolution, future simulation studies and further assessments of these statistical methods are necessary to understand the consequences of both violating and blindly following simple guidelines.

scholarly journals Properties of the full random effect modelling approach with missing covariates

2019 ◽  
Author(s):  
Joakim Nyberg ◽  
E. Niclas Jonsson ◽  
Mats O. Karlsson ◽  
Jonas Häggström ◽  
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Random Effect ◽  
Simulated Data ◽  
Reference Method ◽  
Parameter Estimates ◽  
Full Model ◽  
Covariate Data ◽  
Model Method ◽  
Covariate Information

SummaryTwo full model approaches was compared with respect to their ability to handle missing covariate information. The reference data analysis approach was the full model method in which the covariate effects are estimated conventionally using fixed effects, and missing covariate data is imputed with the median of the non-missing covariate information. This approach was compared to a novel full model method which treats the covariate data as observed data and estimates the covariates as random effects. A consequence of this way of handling the covariates is that no covariate imputation is required and that any missingness in the covariates is handled implicitly. The comparison between the two analysis methods was based on simulated data from a model of height for age z-scores as a function of age. Data was simulated with increasing degrees of randomly missing covariate information (0-90%) and analyzed using each of the two analysis approaches. Not surprisingly, the precision in the parameter estimates from both methods decreased with increasing degrees of missing covariate information. However, while the bias in the parameter estimates increased in a similar fashion for the reference method, the full random effects approach provided unbiased estimates for all degrees of covariate missingness.

Intratree and intertree variation in selected wood quality characteristics of European oak (Quercuspetraea and Quercusrobur)

1994 ◽  
Vol 24 (9) ◽  
pp. 1818-1823 ◽  
Author(s):  
S.Y. Zhang ◽  
G. Nepveu ◽  
R. Eyono Owoundi
Keyword(s):  
Total Variation ◽  
Wood Density ◽  
Wood Quality ◽  
Ring Width ◽  
Relative Magnitude ◽  
Tree Age ◽  
Cambial Age ◽  
Latewood Density ◽  
European Oak ◽  
Intratree Variation

Twenty-three trees of European oak (Quercuspetraea (Matt) Liebl. and Quercusrobur L.) were collected from northeastern France to study intratree and intertree variation in the following characteristics: (i) wood density as well as earlywood density and latewood density; (ii) various types of wood shrinkage; and (iii) ring width and its components. Both intratree variation and intertree variation in the three characteristics are significant, but intertree variation is generally smaller. However, the relative magnitude of intertree variation varies with characteristic: intertree variation accounts for about 40% of the total variation in radial, tangential, and volumetric wood shrinkage, 32.5% of the total variation in ring width, and 12.6% of the total variation in wood density. Furthermore, the intertree variation is closely and positively related to the intratree variation: among the three characteristics studied, both intertree variation and intratree variation were highest for ring width and its components, and lowest for wood density and its components. In addition, intratree variation increased remarkably with increasing tree age in these species. In general, intratree variation in wood density and wood shrinkage depends more on cambial age than on ring width. The present study, together with the information available so far, suggests that the quality of European oak wood could be significantly improved.

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