A neural model approach for regularization in the mean estimation case

2010 ◽  
Author(s):  
Sergio Decherchi ◽  
Mauro Parodi ◽  
Sandro Ridella
Keyword(s):  
Neural Model ◽  
Mean Estimation ◽  
The Mean ◽  
Model Approach

scholarly journals Neural Model for the Prediction of Volume Losses in the Aging Process of Rums

2020 ◽  
Vol 29 (54) ◽  
pp. e10514
Author(s):  
Beatriz García-Castellanos ◽  
Osney Pérez-Ones ◽  
Lourdes Zumalacárregui-de-Cárdenas ◽  
Idania Blanco-Carvajal ◽  
Luis Eduardo López-de-la-Maza
Keyword(s):  
Aging Time ◽  
Aging Process ◽  
Neural Model ◽  
Correlation Factor ◽  
Coefficient Of Determination ◽  
Training Algorithms ◽  
The Neural Network ◽  
Aging Conditions ◽  
The Mean ◽  
Input Variables

The rum aging process shows volume losses, called wastage. The numerical operation variables: product, boardwalk, horizontal and vertical positions, date, volume, alcoholic degree, temperature, humidity and aging time, recorded in databases, contain valuable information to study the process. MATLAB 2017 software was used to estimate volume losses. In the modeling of the rum aging process, the multilayer perceptron neuronal network with one and two hidden layers was used, varying the number of neurons in these between 4 and 10. The Levenberg-Marquadt (LM) and Bayesian training algorithms were compared (Bay) The increase in 6 consecutive iterations of the validation error and 1,000 as the maximum number of training cycles were the criteria used to stop the training. The input variables to the network were: numerical month, volume, temperature, humidity, initial alcoholic degree and aging time, while the output variable was wastage. 546 pairs of input/output data were processed. The statistical Friedman and Wilcoxon tests were performed to select the best neural architecture according to the mean square error (MSE) criteria. The selected topology has a 6-4-4-1 structure, with an MSE of 2.1∙10-3 and a correlation factor (R) with experimental data of 0.9898. The neural network obtained was used to simulate thirteen initial aging conditions that were not used for training and validation, detecting a coefficient of determination (R2) of 0.9961.

scholarly journals Economics and Technical Efficiency of Maize Production Among Small Scale Farmers in Abuja, Nigeria: Stochastic Frontier Model Approach

2020 ◽  
Vol 2 (6) ◽  
Author(s):  
E. S. Ebukiba ◽  
L. Anthony ◽  
S. M. Adamu
Keyword(s):  
Stochastic Frontier ◽  
Farm Size ◽  
Small Scale ◽  
Stochastic Frontier Model ◽  
Gross Margin ◽  
Maize Production ◽  
Factors Influencing ◽  
The Mean ◽  
Small Scale Farmers ◽  
Model Approach

This study evaluated Economics and Technical Efficiency of Maize Production Among Small Scale Farmers in Abuja, Nigeria; Stochastic Frontier Model Approach; Multi-stage sampling technique was adopted and used. Primary data were collected through the use of well-structured questionnaire from one hundred and fifty (150) sampled respondents in the study area. Data were analyzed to achieve the specified objectives using the following tools of analysis, Descriptive Statistics, Stochastic Frontier, Gross Margin Analysis, Financial Analysis, Five Point Likert Scale, and Principal Components Analysis. The results show that majority 40.47% of the sampled respondents were among the age range of 41-50 years of age and 25.33% were within the age bracket of 31-40 years of age. The mean age of the sampled farmers is 44 years. Which indicated that Young and energetic farmers are able to withstand stress and adopt new innovations. Most 88.67% of the farmers were male. Majority 72.67% were married. The mean household size of the sampled respondents is 6 members per family. Majority (67%) of the small-scale maize farmers had 1-2 ha of land and the average farm size cultivated by the farmers was 2.576 ha. The factors influencing total output of maize were seed input (P<0.01), Farm Size (P<0.05), quantity of fertilizer (P<0.05), and labour input (P<0.01) were statistically significant variables. The results of the inefficiency components show that the factors influencing technical inefficiency includes: age (P<0.01), education (P<0.01), access to credit (P<0.05), farming experience, and household size (P<0.05) and were statistically significant. The total revenue realized by the sampled small-scale maize farmers was N238,317 on average. While the total variable costs on average basis was N109,702.93. The gross margin realized was N128667.07. The gross margin ratio was 0.54 while operating ratio calculated was 0.857 and the rate of return on investment (RORI) was 1.17. The retained component from the constraint’s analysis include Lack of Improve Seed, Lack of Transportation, Poor Storage Facilities, Inadequate Capital, and Cattle Herdsmen. The retained components explained 60% of the variation of the component included in the model. The study therefore, recommends that affordable loans and adequate capital should be made available to the small-scale maize farmers, farmers should be properly trained and educated by the non-governmental organizations and extension agents on chemical application, fertilizer use and pests and diseases control measures especially on integrated pest management (IPM). Inputs like improve seeds, fertilizer, and chemicals should be made available to farmers at subsidized rates and at appropriate time coinciding with production periods for proper usage. Provisions should be made for transportation and storage facilities for farmers, the issue of conflict between farmers and herdsmen should be brought to book and resolved amicably for peaceful coexistence.

scholarly journals Nelson-Siegel Model Approach to the Euro Area Yield Curves

2017 ◽  
Vol 56 (1) ◽  
pp. 53-63
Author(s):  
Akvilė Mazanauskaitė
Keyword(s):  
Euro Area ◽  
Static Model ◽  
Yield Curves ◽  
Treasury Bills ◽  
Best Fitting ◽  
The Mean ◽  
Model Approach

In this paper Nelson-Siegel model has been examined. The main purpose of this paper is to fit the best Nelson-Siegel model to the Euro Area yield curves and to compare with Lithuanian yields in order to draw conclusions about readiness of Lithuania to join the Euro Area. In order to succeed in achieving the goal, Euro Area zero coupon bonds have been examined and various static Nelson-Siegel models were developed. Also, the mean of absolute errorof the Lithuanian government treasury bills was calculated using the best-fitting Nelson-Siegel model of the Euro Areayields. The results have shown that if the static model is calculated for each year, the yield are described precisely in the model.

scholarly journals Estimations of fibre trait stability and type of inheritance in cotton

2018 ◽  
Vol 54 (No. 4) ◽  
pp. 190-192 ◽  
Author(s):  
Vasileios Greveniotis ◽  
Evangelia Sioki ◽  
Constantinos G. Ipsilandis
Keyword(s):  
Stability Index ◽  
Quality Trait ◽  
Quality Traits ◽  
Quantitative Inheritance ◽  
Fibre Quality ◽  
Mean Estimation ◽  
Trait Stability ◽  
Genotype Evaluation ◽  
The Mean ◽  
Almost All

Traits affecting fibre quality were evaluated in a multi-location environmental experiment. Four main cotton regions in Greece were selected as different environments. Five commercial cotton cultivars were used for evaluation of 10 fibre quality traits. Each cultivar was sown in 10 different fields in each region. Environmental fluctuations within regions affected each quality trait differently showing a different degree of inheritance. Four traits showed the lowest stability index values indicating quantitative inheritance, further four traits with intermediate values indicated determination by a few genes, while the more stable and thus with qualitative inheritance traits were considered to indicate fibre maturity and uniformity. The mean estimation of stability in multi-location experiments was found the same as in multi-genotype evaluation. Two cultivars (Elsa and Celia) were found to be more stable across the Greek environments and two regions favoured stability for almost all traits. Correlations between regions were high and the same was found between genotypes.  

scholarly journals Sample size to estimate the mean of morphological traits of rye cultivars in sowing dates and evaluation times

2018 ◽  
Vol 39 (2) ◽  
pp. 521
Author(s):  
Cirineu Tolfo Bandeira ◽  
Alberto Cargnelutti Filho ◽  
Diego Nicolau Follmann ◽  
Cláudia Marques de Bem ◽  
Cleiton Antonio Wartha ◽  
...  
Keyword(s):  
Sample Size ◽  
Plant Height ◽  
Morphological Traits ◽  
Initial Evaluation ◽  
Estimation Errors ◽  
Mean Estimation ◽  
Sowing Dates ◽  
Number Of Leaves ◽  
Size Variability ◽  
The Mean

The objectives of this study were to determine the sample size (number of plants) required to estimate the mean of morphological traits of rye (Secale cereale L.) and verify the sample size variability between the traits, cultivars, sowing dates, and evaluation times for distincts mean estimation errors. Ten uniformity trials were performed with two rye cultivars (BRS Progresso and Temprano) in five sowing dates (05/03/2016, 05/25/2016, 06/07/2016, 06/22/2016 and 07/04/2016). Evaluations of traits plant height, number of leaves, and number of stems were performed during the development of the crop. In order to verify the difference of the traits between cultivars and between sowing dates and evaluation times, the F-test was applied to test the hypothesis of homogeneity of variances and the Student’s t-test was used to test the hypothesis of equality of means. The sample size of each trait was calculated for distincts mean estimation errors. There is sample size variability between the traits, cultivars, sowing dates, and evaluation times. In order to estimate the mean of plant height with the same precision, smaller sample sizes are required at the intermediate and final evaluation times compared to initial evaluation times. For the traits number of leaves and stems, smaller sample sizes are required in the initial evaluation times than in the final evaluation times. For mean estimation of traits with maximum estimation error of 15% between sowing dates and evaluation times, 83 and 103 plants are required respectively for cultivars BRS Progresso and Temprano.

Ratio methods to the mean estimation with known quantiles

2005 ◽  
Vol 170 (2) ◽  
pp. 1031-1044 ◽  
Author(s):  
M. Rueda ◽  
A. Arcos ◽  
S. González-Aguilera ◽  
M.D. Martínez-Miranda ◽  
Y. Román ◽  
...  
Keyword(s):  
Mean Estimation ◽  
The Mean

scholarly journals Modelling the potential distribution and habitat suitability of the alien fungus Clathrus archeri in Romania

2021 ◽  
Vol 45 (2) ◽  
pp. 241-250
Author(s):  
Ciprian Bîrsan ◽  
Constantin Mardari ◽  
Ovidiu Copoţ ◽  
Cătălin Tănase
Keyword(s):  
Habitat Suitability ◽  
Potential Distribution ◽  
Rapid Expansion ◽  
Distribution Area ◽  
Maximum Entropy Model ◽  
Invasive Potential ◽  
Entropy Model ◽  
The Mean ◽  
Suitable Habitats ◽  
Model Approach

Clathrus archeri is a saprophytic fungus native to the southern hemisphere which was introduced in Europe in the early twentieth century. Although it is naturalized in most regions of Central Europe, in Romania it is considered rather a rare species because it has been identified in only a few localities. Because of the rapid expansion of its range throughout Europe some authors assign this species an invasive potential. The objective of the paper was to identify both the potential distribution area and the potential suitable habitats for expansion in Romania and to highlight the environmental variables driving the probability of its occurrence. The maximum entropy model approach implemented in Maxent was used to model the species? potential distribution. The results highlighted altitude, snow cover length, the mean temperature of the driest quarter, and precipitation in the coldest quarter as the most important predictors of species? potential distribution in Romania. The map of the predicted distribution showed that the highest probability of occurrence for this species is in the mountainous and adjacent areas, while the map of habitat suitability confirmed that the best environmental conditions are in the Carpathians, while the most unfavourable are in the south-eastern regions of the country.

scholarly journals Optimal two-stage sampling for mean estimation in multilevel populations when cluster size is informative

2020 ◽  
pp. 096228022095283
Author(s):  
Francesco Innocenti ◽  
Math JJM Candel ◽  
Frans ES Tan ◽  
Gerard JP van Breukelen
Keyword(s):  
Cluster Size ◽  
Simple Random Sampling ◽  
Equal Probability ◽  
Outcome Variable ◽  
Two Stage ◽  
Mean Estimation ◽  
Informative Cluster Size ◽  
The Mean ◽  
Two Stages ◽  
Number Of Individuals

To estimate the mean of a quantitative variable in a hierarchical population, it is logistically convenient to sample in two stages (two-stage sampling), i.e. selecting first clusters, and then individuals from the sampled clusters. Allowing cluster size to vary in the population and to be related to the mean of the outcome variable of interest (informative cluster size), the following competing sampling designs are considered: sampling clusters with probability proportional to cluster size, and then the same number of individuals per cluster; drawing clusters with equal probability, and then the same percentage of individuals per cluster; and selecting clusters with equal probability, and then the same number of individuals per cluster. For each design, optimal sample sizes are derived under a budget constraint. The three optimal two-stage sampling designs are compared, in terms of efficiency, with each other and with simple random sampling of individuals. Sampling clusters with probability proportional to size is recommended. To overcome the dependency of the optimal design on unknown nuisance parameters, maximin designs are derived. The results are illustrated, assuming probability proportional to size sampling of clusters, with the planning of a hypothetical survey to compare adolescent alcohol consumption between France and Italy.

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