scholarly journals Prediction of Birth Weight of Newborn Nepalese’ Babies by Maximum Likelihood Estimation

2020 ◽  
pp. 8-15
Author(s):  
Govinda Prasad Dhungana
Keyword(s):  
Birth Weight ◽  
Maximum Likelihood ◽  
Low Birth Weight ◽  
Normal Distribution ◽  
Newborn Infants ◽  
Likelihood Estimation ◽  
Standard Normal Distribution ◽  
Average Weight ◽  
High Birth Weight ◽  
Data Set

The first weight of newborn babies is a vital indicator of their growth and progress in the performance of their life span. Normal birth weight children are healthier than low birth weight and overweight. Total 1111 data were taken from the 2016 NDHS data set and the R environment used to estimate the average birth of newborn babies. The maximum likelihood estimate of normal distribution is used to determine the average (SD) weight of newborn babies. The estimated value is validation by KS test and pdf plot with normal curve. Prevalence of low birth weight and overweight from the standard normal distribution has also been predicted. The mean weight of newborn infants of the children is (2.94 kg) 2940 grams and the standard deviation is (0.573 kg) 573 grams. The percentage of low birth weight and high birth weight is 22.04% and 3.14% respectively. The average weight of Nepalese newborn babies is ordinary, but the prevalence of low birth weight is still high in Nepal.

scholarly journals On Properties of the Bimodal Skew-Normal Distribution and an Application

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 703
Author(s):  
David Elal-Olivero ◽  
Juan F. Olivares-Pacheco ◽  
Osvaldo Venegas ◽  
Heleno Bolfarine ◽  
Héctor W. Gómez
Keyword(s):  
Maximum Likelihood ◽  
Normal Distribution ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Real Data ◽  
Skew Normal Distribution ◽  
Data Set ◽  
Normal Distributions ◽  
Stochastic Representations ◽  
Skew Normal

The main object of this paper is to develop an alternative construction for the bimodal skew-normal distribution. The construction is based upon a study of the mixture of skew-normal distributions. We study some basic properties of this family, its stochastic representations and expressions for its moments. Parameters are estimated using the maximum likelihood estimation method. A simulation study is carried out to observe the performance of the maximum likelihood estimators. Finally, we compare the efficiency of the new distribution with other distributions in the literature using a real data set. The study shows that the proposed approach presents satisfactory results.

scholarly journals Low Birth Weight Prevalence in Children Diagnosed with Neurodevelopmental Disorders in Dubai

2021 ◽  
Vol 8 ◽  
pp. 2333794X2110317
Author(s):  
Faisal A. Nawaz ◽  
Meshal A. Sultan
Keyword(s):  
Risk Factors ◽  
Birth Weight ◽  
Mental Disorders ◽  
Low Birth Weight ◽  
Neurodevelopmental Disorders ◽  
Autism Spectrum ◽  
High Birth Weight ◽  
Perinatal Risk Factors ◽  
Perinatal Risk ◽  
The Impact

The aim of this study is to evaluate the prevalence of low birth weight and other perinatal risk factors in children diagnosed with neurodevelopmental disorders. This is one of the first studies in the Arabian Gulf region focused on the contribution of these factors toward the development of various disorders such as attention-deficit/hyperactivity disorder, autism spectrum disorder, and other mental disorders. This descriptive study was based on qualitative data analysis. We reviewed retrospective information from the electronic medical records of 692 patients in Dubai, United Arab Emirates. The prevalence of low birth weight in children with mental disorders was significantly higher as compared to the general population (16% vs 6% respectively). Furthermore, other risk factors, including high birth weight and preterm birth were noted to have a significant association with neurodevelopmental disorders. Future research on the impact of perinatal risk factors will contribute to advancement of early intervention guidelines.

scholarly journals Maximum Likelihood Estimation of the VAR(1) Model Parameters with Missing Observations

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Helena Mouriño ◽  
Maria Isabel Barão
Keyword(s):  
Stochastic Process ◽  
Missing Data ◽  
Maximum Likelihood ◽  
Moving Average ◽  
Practical Importance ◽  
Likelihood Estimation ◽  
Model Parameters ◽  
Missing Observations ◽  
Data Set ◽  
The Impact

Missing-data problems are extremely common in practice. To achieve reliable inferential results, we need to take into account this feature of the data. Suppose that the univariate data set under analysis has missing observations. This paper examines the impact of selecting an auxiliary complete data set—whose underlying stochastic process is to some extent interdependent with the former—to improve the efficiency of the estimators for the relevant parameters of the model. The Vector AutoRegressive (VAR) Model has revealed to be an extremely useful tool in capturing the dynamics of bivariate time series. We propose maximum likelihood estimators for the parameters of the VAR(1) Model based on monotone missing data pattern. Estimators’ precision is also derived. Afterwards, we compare the bivariate modelling scheme with its univariate counterpart. More precisely, the univariate data set with missing observations will be modelled by an AutoRegressive Moving Average (ARMA(2,1)) Model. We will also analyse the behaviour of the AutoRegressive Model of order one, AR(1), due to its practical importance. We focus on the mean value of the main stochastic process. By simulation studies, we conclude that the estimator based on the VAR(1) Model is preferable to those derived from the univariate context.

Birth Weight and Childhood Growth

PEDIATRICS ◽  
1988 ◽  
Vol 82 (6) ◽  
pp. 828-834
Author(s):  
Nancy J. Binkin ◽  
Ray Yip ◽  
Lee Fleshood ◽  
Frederick L. Trowbridge
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Strong Predictor ◽  
Full Range ◽  
Birth Certificate ◽  
High Birth Weight ◽  
Growth Data ◽  
Low Birth Weight Infants ◽  
Childhood Growth ◽  
Supplemental Food

Most previous studies of the relationship between birth weight and childhood growth have concentrated on the growth of low birth weight infants. To examine this relationship throughout the full range of birth weights, growth data for children <5 years of age from the Tennessee Special Supplemental Food Program for Women, Infants, and Children linked to birth certificate records for 1975 to 1985 were used. Growth status was compared for 500-g birth weight categories from 1,000 g to 4,999 g using mean Z scores and the percentage of children more than 2 SD above or less than 2 SD below the median for height for age, weight for age, and weight for height. Infants with lower birth weights were likely to remain shorter and lighter throughout childhood, especially those who were intrauterine growth retarded rather than premature. Conversely, those infants with higher birth weights were likely to remain taller and heavier and to have a higher risk of obesity. Birth weight is a strong predictor of weight and height in early childhood, not only for low birth weight children but also for those of normal and high birth weight.

Utilizarea teoriei valorilor extreme în climatologie

2019 ◽  
Author(s):  
Valentin Raileanu ◽  
Keyword(s):  
Maximum Likelihood ◽  
Extreme Values ◽  
Probability Distributions ◽  
Simulated Data ◽  
Likelihood Estimation ◽  
R Software ◽  
Data Set ◽  
Data Format ◽  
Generalized Pareto ◽  
Distribution Parameters

The article briefly describes the history and fields of application of the theory of extreme values, including climatology. The data format, the Generalized Extreme Value (GEV) probability distributions with Bock Maxima, the Generalized Pareto (GP) distributions with Point of Threshold (POT) and the analysis methods are presented. Estimating the distribution parameters is done using the Maximum Likelihood Estimation (MLE) method. Free R software installation, the minimum set of required commands and the GUI in2extRemes graphical package are described. As an example, the results of the GEV analysis of a simulated data set in in2extRemes are presented.

Antibody to varicella zoster virus in low-birth-weight newborn infants

1978 ◽  
Vol 93 (3) ◽  
pp. 505-506 ◽  
Author(s):  
Richard K. Raker ◽  
Sharon Steinberg ◽  
Lewis M. Drusin ◽  
Anne Gershon
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Varicella Zoster Virus ◽  
Newborn Infants ◽  
Varicella Zoster

Cryptorchidism in the Newborn

PEDIATRICS ◽  
1973 ◽  
Vol 51 (2) ◽  
pp. 310-311
Author(s):  
Alfredo Santesteban
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Recent Article ◽  
Newborn Infants ◽  
Review Of The Literature ◽  
Undescended Testes ◽  
Low Birth Weight Infant ◽  
New Born ◽  
Born Infant ◽  
Infant Birth

The incidence of cryptorchidism in newborn infants is stated to be 3% to 4% by Curran and Curran in a recent article.1 The reference cited is a report by Scorer published in 1957.2 However, a review of the literature shows that the incidence of cryptorchidism in the full-term new born infant is slightly lower and in the low birth weight infant (birth weight 2,500 gm or less), it is considerably higher. Up until 1955 there was much confusion regarding the incidence of undescended testes in the newborn.

Abstract MP031: Birth Weight, Genetic-Susceptibility and Adulthood Risk of Type 2 Diabetes

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Yanping Li ◽  
Qibin Qi ◽  
Tsegaselassie Workalemahu ◽  
Frank B Hu ◽  
Lu Qi
Keyword(s):  
Type 2 Diabetes ◽  
Birth Weight ◽  
Low Birth Weight ◽  
Genetic Susceptibility ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Diabetes Risk ◽  
High Birth Weight ◽  
Genotype Score

Background: Both stressful intrauterine milieus and genetic susceptibility have been linked to later life diabetes risk. The present study aims to examine the interaction between low birth weight, a surrogate measure of stressful intrauterine milieus, and genetic susceptibility in relation to risk of type 2 diabetes in adulthood. Methods: The analysis included two independent, nested case-control studies of in total 2591 cases of type 2 diabetes and 3052 healthy controls from prospective cohorts: the Nurses’ Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). We developed 2 genotype scores using susceptibility loci recently identified through Genome Wide Association Studies: 1) an ‘obesity genotype score’ based on 32 BMI-predisposing single nucleotide polymorphisms (SNPs); and 2) a ‘diabetes genotype score’ based on 35 diabetes-predisposing SNPs. Results: Both the obesity genotype score and diabetes genotype score showed consistently significant association with risk of type 2 diabetes in NHS and HPFS ( P for trend < 0.01). In the pooled sample of the two cohorts, we found significant interaction between birth weight and obesity genotype score in relation to type 2 diabetes ( P for interaction=0.017). In low birth weight individuals (≤ 2.5 kg), the multivariable-adjusted odds ratio (OR) was 2.55 (95% confidence interval [CI]: 1.34–4.84) in the comparison of the highest with the lowest quartile of the obesity genotype score, while the OR was 1.27 (95%CI: 1.04–1.55) among individuals with birth weight above 2.5kg. Diabetes genotype score also showed stronger association with type 2 diabetes risk in individuals with low birth weight than those with high birth weight. Comparing individuals of the highest with the lowest quartile of the diabetes genotype score, the multivariable-adjusted odds ratio was 3.80 (95%CI: 1.76–8.24) among individuals with low birth weight and was 2.27 (95%CI: 1.82–2.83) among those with high birth weight. However, test for interaction was marginal ( P =0.16). Conclusion: Our data suggest low birth weight and genetic susceptibility to obesity may synergistically affect adulthood risk of type 2 diabetes.

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