Likelihood Procedure Research Articles

Genetic parameter estimation of preweaning growth traits in Akkaraman sheep.

This study aimed to evaluate (co)variance components and heritability of pre-weaning body weight traits and the Kleiber ratio in Akkaraman sheep. Data collected between 2018 and 2023 from Çankırı province, Türkiye, formed the basis of this research. The considered traits were birth weight (BW), weaning weight (WW), average pre-weaning daily weight gain (ADWG), and Kleiber ratio (KR). Utilizing animal mixed models and the average information restricted maximum likelihood (AI-REML) procedure, genetic parameters were estimated. Direct heritability estimates were 0.30 ± 0.02, 0.23 ± 0.02, 0.23 ± 0.02, and 0.28 ± 0.03 for BW, WW, ADWG, and KR, respectively. Maternal genetic heritabilities were 0.03 for WW and 0.02 for WW, ADWG, and KR. Direct genetic correlations among pre-weaning growth traits were negative for BW-WW and BW-ADWG and positive for WW-ADWG at -0.05, -0.23, and 0.98, respectively. The moderate direct heritability estimate suggests the presence of genetic variability in the Akkaraman sheep breed, indicating potential genetic progress through selective breeding. Despite the low maternal permanent environmental effects, the significant impact of maternal care on lamb growth in this breed underscores the importance of considering both direct and maternal effects in the genetic evaluation of early growth traits. The observed negative genetic correlations among birth weight, weaning weight, and daily live weight gain until weaning emphasize the need for careful consideration in selection programs for the Akkaraman breed.

Estimates of genetic parameters and genetic trends for growth traits in Menz sheep under community-based breeding programs

The main objectives of this study were to estimate genetic and phenotypic parameters for growth traits in Menz sheep under community-based breeding programs (CBBPs). Data used in the study were collected from five Menz CBBPs villages during 15-year period (2009–2023). Studied growth traits were birth weight (BW), weaning weight (WW), six-month weight (6 MW), yearling weight (YW), Average daily gain from birth to weaning (ADG1), average daily gain from weaning to six months (ADG2) and average daily gain from six months to yearling (ADG3). Fixed effects were estimated using the GLM procedure of SAS 9.4. Genetic parameters were estimated fitting different univariate animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure with WOMBAT software. The most appropriate model for each trait was determined applying likelihood ratio tests. Model including only direct additive genetic effect was the most appropriate model for BW, YW, ADG2 and ADG3, whereas model including direct additive and maternal additive genetic effect without taking into account covariance between them was the most appropriate for WW, 6 MW and ADG1. Based on the most appropriate models, direct heritability of BW, WW, 6 MW, YW, ADG1, ADG2 and ADG3 were 0.29 ± 0.01, 0.45 ± 0.01, 0.46 ± 0.02, 0.42 ± 0.02, 0.44 ± 0.01, 0.75 ± 0.02 and 0.21 ± 0.02, respectively. The estimated maternal heritability were 0.04 ± 0.01, 0.02 ± 0.01 and 0.02 ± 0.01 for WW, 6 MW and ADG1, respectively. Additive coefficient of variance were ranged from 9.53 % for BW to 33.02 % for ADG2. Moderate to higher estimates of direct heritability and additive coefficient of variation (CVA) in the current study indicates higher potential for genetic improvement of studied traits through direct selection. The genetic trend for the Menz sheep's six-month weight in Molale CBBPs village reveals a promising annual growth rate of 0.20 kg. Optimizing the ongoing breeding program into specializing-sire producer groups and applying intensive selection on the sub-nucleus flock could improve the efficiency of the breeding program. Genetic correlations among the studied traits were ranged from −0.50 for ADG-ADG2 to 0.98 for WW-ADG1. Genetic correlation between 6 MW and other studied traits was positive and moderate in magnitude. To achieve optimum genetic gain, the implemented selection criteria for Menz sheep (6 MW) should be continued.

Evaluating animal models comprising additive genetic and maternal effects on growth traits in German Angora rabbit

This investigation was carried out to estimate the genetic parameters for German Angora rabbits using most appropriate animal model comprising additive and maternal effects. The pedigree information and data on growth traits were collected from 5221 rabbits, which descended from 699 does and 294 bucks over a period of 21 yr (2001–2021) kept at Northern Temperate Regional Station, Garsa, Kullu (Himachal Pradesh), India. The average daily gain (ADG) and Kleiber ratio (KR) were calculated at different age intervals. Analyses were carried out by restricted maximum likelihood procedure fitting six animal models with various combinations of direct and maternal effects. The best model was evaluated on the basis of a likelihood ratio test. Analysis revealed that the model including both direct and maternal genetic effects along with permanent effect of the dam was most suitable for all traits except for body weight (BW) at 6th wk of age, ADG from 6th to 12th wk of age and KR associated to ADG from 12th to 18th wk of age. The direct heritability estimates from the best model were ranged from, 0.34±0.05 to 0.49±0.05 for BW; 0.19±0.04, to 0.46±0.06 for ADG and 0.21±0.04 to 0.41±0.05 for KR, respectively. Direct heritability estimates were overestimated when maternal effects were ignored. Maternal effects on BW declined from 0.49±0.04 at weaning to 0.06±0.03 at 12th wk of age and 0.09±0.04 at 18th wk of age. Correlations between direct and maternal effects ranged from −0.44±0.15 to−0.52±0.14 for body weights, indicating biological antagonism between these effects. Genetic correlations among various growth traits were positive and high, indicating scope for correlated response in later expressed traits. Analysis revealed that maternal additive influences were only important until weaning, whereas permanent environmental maternal influences were present in all growth traits considered in this study. The moderate estimates of heritability for growth traits and Kleiber ratio of rabbit in this study indicate that rates of genetic progress may be possible for these traits by selection under the standard management system.

Reliability inference of a multicomponent stress-strength model for exponentiated Pareto distribution based on progressive first failure censored samples

Multicomponent stress-strength (MC-SS) analysis is crucial for risk management and decision-making in various fields such as engineering, manufacturing, and quality control. It helps in identifying vulnerable components and areas where improvements can enhance overall system reliability. A primary contribution of this research is the implementation of the progressive first-Failure censored (PFIF-C) scheme. This scheme offers a novel and efficient approach to time and cost censoring, surpassing many existing censoring schemes found in the literature. The current study investigates the issue of MC-SS reliability inference under PFIF-C from the exponentiated Pareto distribution. The reliability of the MC-SS system is considered under the condition that both stress and strength follow an exponentiated Pareto distribution with a common second shape parameter. The parameter estimates and reliability estimate of the MC-SS system is produced using the maximum likelihood and Bayesian procedures. The asymptotic confidence intervals and highest posterior density credible intervals for the MC-SS system reliability are produced. Bayesian estimates are yielded using Markov Chain Monte Carlo under both informative and non-informative priors, considering symmetric and asymmetric loss functions. In order to assess the efficacy of the suggested methodology, simulation analyses are conducted. According to the simulation data Bayesian estimates of the MC-SS reliability, employing both symmetric and asymmetric loss functions, consistently outperform maximum likelihood estimates in terms of estimated risks. In general, Bayesian estimates based on asymmetric loss function perform better than the other competing loss function. The procedure is further shown with one real-world data example about failure times of a specific software model to show how the recommended approach may be applied to assess the strength and stress of a multicomponent model.

Group acceptance sampling plan based on truncated life tests for Type-I heavy-tailed Rayleigh distribution

This study on the Type-I heavy-tailed Rayleigh (TI-HTR) distribution is a special case of Type-I heavy-tailed (TI-HT) family of distributions was studied. The characteristics were derived, including the moment and its measures, quantile function, reliability measures, and other statistical properties as well as parameter estimation using the maximum likelihood method and penalized likelihood estimation. The behavior of its various functions were shown graphically. Analytically, we showed that model linearly grows near the origin and exhibits rapid exponential decay. However, the tail behavior cannot equal the traditional heavy-tail in the power law sense, hence it is called the type-I heavy-tail. Interestingly, we designed a group acceptance plan (GASP) and demonstrated usefulness with both assumed and maximum likelihood estimates. The GASP under the TI-HTR distribution is preferable when the parameter values are small. The distribution was used to model real-life data sets to justify its usefulness. The results of the application of the model to both COVID-19 and Cancer data showed that the model fits the two data better than the competing models and also suggest that inference from the model is better than those of the competitors. In estimating the parameters, the penalized likelihood procedure perform considerably better with minimum standard error of the estimates. From the Cramér-von Mises test results which guides against the heavy-tail sensitivity, the TI-HTR distribution offers a better model for fitting fast decaying exponential data since it has the least statistics in both datasets.

Estimates of genetic parameters for growth traits in dorper crossbred sheep population.

The study was carried out to estimate genetic and phenotypic parameters for growth traits in Dorper crossbred sheep. The data set consisted of 5717 growth records from 1347 individuals of Dorper 50% crossbred sheep descended from 43 sires and 344 dams born between the years 2012 and 2022 at Debre Birhan Agricultural Research Center sheep research station, Ethiopia. Studied traits were birth weight (WT0), weaning weight (WT3), six months weight (WT6), yearling weight (WT12), average daily gain from birth to weaning (ADG1), average daily gain from weaning to six months (ADG2), average daily gain from six months to yearling (ADG3). The (co)variance components were estimated by fitting six different univariate animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure. Contrary to the genetic trend, phenotypic performance for all studied traits showed a declining trend over the years. Direct heritability estimates of 0.10 ± 0.06, 0.29 ± 0.09, 0.37 ± 0.10, 0.10 ± 0.09, 0.43 ± 0.15, 0.04 ± 0.05, and 0.14 ± 0.09 were obtained for WT0, WT3, WT6, WT12, ADG1, ADG2 and ADG3, respectively. Genetic correlations among the studied traits ranged from -0.43 (between ADG2 and ADG3) to 0.99 (between WT3 and ADG1). Selection for weaning, six months and pre-weaning average daily gain would be expected to yield good response as these traits were found moderately heritable. Strong to moderate genetic correlation of WT3 with WT6, WT12, and ADG1 suggested that selection based on WT3 would result in improvement of other growth traits due to correlated response.

Spline regression with automatic knot selection

Spline regression has proven to be a useful tool for nonparametric regression. The flexibility of this function family is based on basepoints defining shifts in the behavior of the function – called knots. The question of setting the adequate number of knots and their placement is usually overcome by penalizing over the spline's overall smoothness (e.g. P-splines). However, there are areas of application where finding the best knot placement is of interest. A new method is introduced for automatically selecting knots in spline regression. The approach consists in setting many initial knots and fitting the spline regression through a penalized likelihood procedure called adaptive ridge, which discards the least relevant knots. The method – called A-splines, for adaptive splines – compares favorably with other knot selection methods: it runs way faster (∼10 to ∼400 faster) than comparable methods and has close to equal predictive performance. A-splines are applied to both simulated and real datasets.

Estimation of (co)variance components for body weight traits in intercross synthetic sheep

This study was carried out on the recently developed intercross sheep developed from Bharat merino and Gaddi sSynthetic in the temperate region in the state of Himachal Pradesh of India. Study aimed to estimate the genetic parameters and (co)variance components for body weights at birth (BW) and 3-month (3BW), 6-month (6BW), 9-month (9BW) and 12-month (12BW) month age in a closed flock of intercross sheep maintained at North Temperate Regional Station of ICAR-CSWRI, Garsa, India. Data records on 1505 sheep descended from 565 dams and 154 sires over the period of 10 years were utilized. Data were corrected for possible fixed environmental effects such as lambing year, parity, sex of lamb, ewe weight at lambing for further genetic analysis. The restricted maximum likelihood procedure fitting animal models with different combinations of direct and maternal effects were used for genetic analysis. Analysis revealed significant influences of lambing year, parity, sex of lamb and ewe weight at lambing on studied traits. Direct heritability estimates for BW, 3BW, 6BW, 9BW and 12BW were 0.14±0.04, 0.18±0.05, 0.00±0.04, 0.05±0.05 and 0.05±0.05, respectively. Maternal effects significantly influenced the BW and estimated maternal heritability for the trait was 0.17±0.03. The correlation among body weights were medium to high except between BW and 12BW and it ranged from 0.16±0.51 to 0.99±0.19. Results suggest that maternal effects were important for initial growth performance. The heritability estimates for weaning weight was moderate and its positive association with other growth traits indicated that the present selection practice at six months may be shifted to early selection at weaning weight for further genetic improvement.

Double penalized variable selection for high-dimensional partial linear mixed effects models

In this study, we address the selection of both fixed and random effects in partial linear mixed effects models. By combining B-spline and QR decomposition techniques, we propose a double-penalized likelihood procedure for both estimating and selecting these effects. Furthermore, we introduce an orthogonality-based method to estimate the non-parametric component, ensuring that the fixed and random effects are separated without any mutual interference. The asymptotic properties of the resulting estimators are investigated under mild conditions. Simulation studies are conducted to evaluate the finite sample performance of the proposed method. Finally, we demonstrate the practical applicability of our methodology by analyzing a real data.

Estimation of P(X < Y) Stress–Strength Reliability Measures for a Class of Asymmetric Distributions: The Case of Three-Parameter p-Max Stable Laws

Asymmetric distributions are frequently seen in real-world datasets due to a number of factors, such as sample biases and nonlinear interactions between the variables observed. Thus, in order to better characterize real-world phenomena, studying asymmetric distribution is of great interest. In this work, we derive stress–strength reliability formulas of the type P(X<Y) when both X and Y follow p-max stable laws with three parameters, which are inherently asymmetric. The new relations are given in terms of extreme-value H-functions and have been obtained under fewer parameter restrictions when compared to similar results in the literature. We estimate the parameters of the p-max stable laws by a stochastic optimization method and the stress–strength probability by a maximum likelihood procedure. The performance of the analytical models is evaluated through simulations and real-life dataset modeling.

Genetic parameters for milk yield and reproductive traits in Honduran Holstein cattle.

The aim of this study was to estimate the (co)variance components and genetic parameters for milk yield adjusted to 305d (MY305), calving-to-conception interval (CCI), number of services per conception (NSC) and calving interval (CI) of Honduran Holstein cows, by fitting a bivariate animal model using Maximum Restricted Likelihood procedures. Model included the fixed effects of calving number, the contemporary calving group (farm-season-year of calving and the cow age as covariate). The estimated means and standard deviations for MY, CCI, NSC and CI were, 5098.60 ± 1564.32kg, 168.27 ± 104.71 days, 2.46 ± 1.69 services, and 448.73 ± 109.16 days, respectively; and their estimated heritabilities were 0.21 ± 0.05, 0.03 ± 0.028, 0.02 ± 0.024 and 0.06 ± 0.04, respectively. The genetic correlations between MY305 and CCI, NSC and CI were positive and antagonist, with values of 0.64 ± 0.52, 0.99 ± 0.56, and 0.32 ± 0.24 respectively. Even though moderate to low heritability was estimated for MY305, systematic selection for milk yield, with a reduction in reproductive efficiency, if considered as the only selection criterion is important to be considered. By including reproductive traits and considering permanent environment effects into the breeding program, might yield a slow, but constant and permanent improvement over time.

A conditional approach for regression analysis of case K interval-censored failure time data with informative censoring

This paper discusses regression analysis of case K interval-censored failure time data, a general type of failure time data, in the presence of informative censoring with the focus on simultaneous variable selection and estimation. Although many authors have considered the challenging variable selection problem for interval-censored data, most of the existing methods assume independent or non-informative censoring. More importantly, the existing methods that allow for informative censoring are frailty model-based approaches and cannot directly assess the degree of informative censoring among other shortcomings. To address these, we propose a conditional approach and develop a penalized sieve maximum likelihood procedure for the simultaneous variable selection and estimation of covariate effects. Furthermore, we establish the oracle property of the proposed method and illustrate the appropriateness and usefulness of the approach using a simulation study. Finally we apply the proposed method to a set of real data on Alzheimer's disease and provide some new insights.

On Estimating Multi- Stress Strength Reliability for Inverted Kumaraswamy Under Ranked Set Sampling with Application in Engineering

The terrible operating constraints of many real-world events cause systems to malfunction regularly. The failure of systems to perform their intended duties when they reach their lowest, highest, or both extreme operating conditions is a phenomenon that researchers rarely focus on. The multi-stress strength reliability R=P(W<X<Z)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R = P(W<X<Z)$$\\end{document} is deemed in this study for a component whose strength X falls between two stresses, W, and Z, where X, W, and Z are independently inverted Kumaraswamy distributed. Both maximum likelihood and maximum product spacing procedures are employed to obtain the reliability estimator under simple random sampling (SRS) and ranked set sampling (RSS) methodologies. Four scenarios for reliability estimators are considered. The reliability estimator in the first and second cases can be determined by applying the same sample design (RSS/SRS) to the strength and stress distributions. When the sample data for W and Z originate from RSS while those for X are acquired from SRS, the third reliability estimator is calculated. The drawn data of the strength and stress random variables, which are obtained from SRS and RSS, respectively, are taken into consideration in the final scenario. The effectiveness of the suggested estimators is compared using a comprehensive computer simulation. Lastly, three real data sets have been used to determine reliability estimators.

Varying coefficient panel data models and methods under correlated error components: Application to disparities in mental health services in England

The contribution of this paper is twofold. Firstly, it introduces novel regression models that combine two important areas of the methodological development in panel data analysis, namely a varying coefficient specification and spatial error dependence. The former allows relatively flexible nonlinear interactions; the latter enables spatial correlations of the disturbance and thus differ significantly from the other random effect models in the literature. To estimate the model, a new estimation procedure is established that can be viewed as a generalization of the quasi-maximum likelihood method for a spatial panel data model to the well-known conditional local likelihood procedure. Novel inference methods, particularly variable selection and hypothesis testing of the parameter constancy, are introduced and are shown to be effective under the complex spatial error dependence. Equally importantly, this paper makes a substantial contribution to the understanding of financing and expenditure for health and social care. In particular, we empirically analyze and explain the effects of political ideologies on the local fiscal policy in England, especially the expenditure on mental health services.

ESTIMATION OF EFFICIENCY AND THE IMPACT OF COVID-19 ON THE EFFECT OF ACCESS TO FINANCE ON EFFICIENCY OF SMALL AND MEDIUM ENTERPRISES (SMEs) IN THE WESTERN AREA OF SIERRA LEONE

&lt;p&gt;To estimate efficiency and the impact of COVID-19 on the effect of access to finance on the efficiency of small and medium enterprises (SMEs) in the Western Area of Sierra Leone, the study adopted the stochastic frontier estimation method of determining the efficiency of firms. A model of maximum performance (capacity) was estimated using 450 SMEs randomly selected from the population of registered SMEs in the Western Area of Sierra Leone from 2018 to 2020. The model of net business earnings was estimated using the Maximum Likelihood procedure and the firm efficiencies were consequently estimated. The mean inefficiencies are estimated by various categories, including SMEs' access to bank credit to determine firm characteristics that are associated with higher mean efficiencies. The empirical results reveal that the potential of firms is determined positively by capital productivity and labour productivity and negatively by the experience of firms, the latter results suggesting that more experience does not push their production outwards but inwards. However, other factors found significant in efficiency differences among firms include gender of the head of the SME, educational level, professional training of the firm heads, sector of operation and the area of operation of the SMEs. Moreover, firm mean efficiencies are not found to vary across the three periods 2018, 2019 and 2020, suggesting the COVID-19 pandemic did not affect firm efficiencies.&lt;/p&gt;&lt;p&gt;&lt;br /&gt;&lt;strong&gt;JEL:&lt;/strong&gt; F13, F15&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0787/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Improved estimation of semiparametric dynamic copula models with filtered nonstationarity

This paper considers estimation of short-run dynamics in time series that contain a nonstationary component. We assume that appropriate preliminary methods can be applied to the observed time series to separate short-run elements from long-run slowly evolving secular components, and focus on estimation of the short-run dynamics based on the filtered data. We use a flexible copula-generated Markov model to capture the nonlinear temporal dependence in the short-run component and study estimation of the copula model. Using the rescaled empirical distribution of the filtered data as an estimator of the marginal distribution, Chen et al. (2022) proposed a simple, yet flexible, two-step estimation procedure for the copula model. The two-step estimator works well when the tail dependence is small. However, simulations reveal that the two-step estimator may be biased in finite samples in the presence of tail dependence. To improve the performance of short-term dynamic analysis in the presence of tail dependence, we propose in this paper a pseudo sieve maximum likelihood (PSML) procedure to jointly estimate the residual copula parameter and the invariant density of the filtered residuals. We establish the root-n consistency and asymptotic distribution of the PSML estimator of any smooth functional of the residual copula parameter and invariant residual density. We further show that the PSML estimator of the residual copula parameter is asymptotically normal, with the limiting distribution independent of the filtration. Simulations reveal that in the presence of strong tail dependence, compared to the two-step estimates of Chen et al. (2022), the proposed PSML estimates have smaller biases and smaller mean squared errors even in small samples. Applications to nonstationary macro-finance and climate time series are presented.

Breaking the budget chains: Empowering Iraqi small- and medium-sized enterprises through Beyond Budgeting

Background: Traditional budgeting has faced criticism, leading researchers to explore alternative management control methods such as Beyond Budgeting. Despite its potential benefits, Beyond Budgeting adoption remains limited.Aim: This research investigates Beyond Budgeting’s effect on Iraqi small- and medium-sized enterprise (SME) performance, focusing on competitive advantage.Setting: The study targets Iraqi SMEs, considering their diverse business landscape. A random sample of 353 accountants was chosen from a research community of 22 974 individuals. SPSS and AMOS 26 software and a custom questionnaire were used.Method: The authors conducted multiple linear regression analysis and Structural Equation Modeling to address our study’s objectives. Additionally, we utilised maximum likelihood procedures to assess factor loadings, construct validity and reliability.Results: Beyond Budgeting implementation significantly affected both financial and nonfinancial performance. It demonstrated positive effects on cost leadership and competitive advantage differentiation. However, an indirect negative impact on nonfinancial performance was observed through the influence on cost leadership, suggesting a trade-off between cost reduction and other nonfinancial factors.Conclusion: The study acknowledges limitations in sample size and the need for considering additional factors. Further research is required to understand Beyond Budgeting’s limited adoption in Iraq. The study contributes valuable insights on Beyond Budgeting as a substitute for traditional approaches, benefiting managers and policymakers.Contribution: This study emphasises Beyond Budgeting’s significant impact on Iraqi SME performance, highlighting the relationship between Beyond Budgeting, competitive advantage strategies, financial and nonfinancial performance. The findings provide insights for enhancing budgeting practices in Iraqi SMEs.

Evaluation of models for estimation of genetic parameters for post-weaning body measurements and their association with yearling weight in Nellore sheep.

The objective of this study was to obtain (co) variance components and genetic parameter estimates for post-weaning body measurements such as body length (BL), height at withers (HW), and chest girth (HG) recorded at six (SBL, SHW, and SHG), nine (NBL, NHW, and NHG) and twelve (YBL, YHW, and YHG) months of age along with yearling weight (YW) in Nellore sheep maintained at livestock research station, Palamaner, Andhra Pradesh, India and also the association among body measurements with YW was studied. Data on 2,076 Nellore sheep (descended from 75 sires and 522 dams) recorded between 2007 and 2016 (10 years) were utilized in the study. Lambing year, sex of lamb, season of lambing and parity of dam were included in the model as fixed effects and ewe weight was kept as a covariate. Analyses were conducted with six animal models with different combinations of direct and maternal genetic effects using restricted maximum likelihood procedure. Best model for each trait was determined based on Akaike's information criterion. Moderate estimates of direct heritability were obtained for the studied traits viz., BL (0.02 to 0.24), HW (0.31 to 0.49), and CG (0.08 to 0.35) and their corresponding maternal heritability estimates were in the range of 0.00 to 0.07 (BL), 0.13 to 0.17 (HW), and 0.07 to 0.13 (CG), respectively. Positive direct genetic and phenotypic correlations among the traits and they ranged from 0.07 (YBL-YW) to 0.99 (SBL-SHG, SHG-YW, and NBL-YBL) and 0.01 (SBL-YBL) to 0.99 (NBL-NHG), respectively. Further, the genetic correlations among all the body measurements and YW were positive and ranged from 0.07 (YW and YBL) to 0.99 (YW and SHG). There was a strong association of chest girth at six months with YW. Further, it is indicated that moderate improvement of post-weaning body measurements in Nellore sheep would be possible through selection.

Estimation of genetic parameters for growth traits and kleiber ratio in dorper sheep breed

The study aimed to estimate genetic and phenotypic parameters for growth traits and Kleiber ratio in Dorper sheep breed. Data used in this study were collected over 12 years (2012–2023) at Debre Birhan Agricultural Research Center sheep research station in Ethiopia. Studied traits were body weights at birth (WT0), weaning (WT3), six month (WT6), and yearling (WT12) age; average daily gains from birth to weaning (ADG0-3), from weaning to six months (ADG3-6), from six months to yearling (ADG6-12); and Kleiber ratios from birth to weaning (KR1) and from weaning to six months (KR2). The (co)variance components were estimated with different animal models using Average Information Restricted Maximum Likelihood (AI-REML) procedure. The best-fitted model for each trait was determined using likelihood ratio tests. Phenotypic performance for WT3, WT6, WT12, ADG0-3 and ADG3-6 showed a decline trend at a rate of 0.216 kg, 0.794 kg, 0.671 kg, 2.601 g and 4.865 g over years respectively. However, WT3, WT6, WT12, ADG0-3 showed a positive genetic improvement trend at a rate of 0.029 kg, 0.043 kg, 0.049 kg and 0.257 g over years respectively. Year of birth had a significant effect (P < 0.001) on all studied traits. Model including direct genetic as well as permanent environmental effect (Model 2) was chosen as the most appropriate model for WT0. Model which included only direct genetic effect (Model 1) was the best-fit model for all other studied traits. Direct heritability estimates based on suitable models were 0.07 ± 0.06, 0.11 ± 0.06, 0.09 ± 0.07, 0.11 ± 0.09 0.11 ± 0.06, 0.00 ± 0.04, 0.15 ± 0.07 and 0.00 ± 0.04 for WT0, WT3, WT6, WT12, ADG0-3, ADG3-6, KR1 and KR2 respectively. The variance ratio for the permanent environmental effect was 0.13 ± 0.04 for WT0. Genetic correlations among the traits ranged from negative (−0.39) for WT0-KR1 to high (0.99) for WT3-ADG0-3 and phenotypic correlations ranged from negative (−0.31) for WT0-KR1 to high (0.98) for WT3-ADG0-3. The low direct heritability estimates for the studied traits indicated that genetic improvement by direct selection might be difficult. Further investigation for the unexpected declined trend of phenotypic performance over years need to be required.

Estimation of Efficiency and the Effect of Access to Finance on Efficiency of Small and Medium Enterprises (SMES) in the Western area of Sierra Leone

Abstract To estimate the efficiency of SMEs and the effect of access to finance on the efficiency of SMEs the study adopted the stochastic frontier estimation method of determining efficiency of firms. A model of maximum performance (capacity) was estimated using 450 SMEs randomly selected from the population of registered SMEs in the Western Area of Sierra Leone from 2018 to 2020. The model of net business earnings was estimated using the Maximum Likelihood procedure and the firm efficiencies were consequently estimated. The mean inefficiencies are estimated by various categories, including SMEs access to bank credit to determine firm characteristics that are associated with higher mean efficiencies. The empirical results reveal that the potential of firms is determined positively by capital productivity and labour productivity and negatively by experience of firms, the latter results suggesting that more experience (in terms of age) does not push their production outwards but inwards. However, other factors are found significant in efficiency differences among firms. These are: gender of the head of the SME, educational level, professional training of the firm heads, sector of operation and the area of operation. JEL classification numbers: F14, F18, G14, G21. Keywords: Efficiency, Finance, Small and Medium Enterprises.