Estimate the probability density function of maximum temperature for the Middle East

2020 ◽  
Vol 29 (4) ◽  
pp. 517-531
Author(s):  
Iqbal Al-Ataby ◽  
Amani Al-Tmimi
Keyword(s):  
Middle East ◽  
Goodness Of Fit ◽  
Heat Waves ◽  
Probability Distributions ◽  
Temperature Data ◽  
Maximum Temperature ◽  
Logistic Distribution ◽  
Recent Past ◽  
Ecmwf Model ◽  
Best Fit

Pollution is one reasons for increase temperature which leads to increase the heat waves which have large socioeconomic and healthy impacts on Middle East. By using monthly daily mean of maximum temperature (C°) at height (2m) covered middle east as a grid of (1581) points for selected months (March, April, May) represent spring and (Jun, July, August) represent Summer for the period 1979 to2018, from the ECMWF, model ERA-interim. Many PDFs have been proposed in recent past, but in present study Logistic, Rayleigh and Gamma distribution are used to describe the characteristics of maximum temperature. This paper attempts to determine the best fitted probability distribution of maximum temperature. To check the accuracy of the predicted data using theoretical probability distributions the goodness of fit criteria Z-test used in this paper. According to the goodness-of-fit criteria and from the graphical comparisons it can be said that Logistic distribution provides the best fit for the observed monthly daily mean of maximum temperature data.

scholarly journals Estimating the Best-Fitted Probability Distribution for Monthly Maximum Temperature at the Sylhet Station in Bangladesh

2021 ◽  
Vol 2 (2) ◽  
pp. 60-67
Author(s):  
Rashidul Hasan Rashidul Hasan
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Probability Model ◽  
Temperature Data ◽  
Maximum Temperature ◽  
Chi Square ◽  
Goodness Of Fit Tests ◽  
Anderson Darling ◽  
Log Normal

The estimation of a suitable probability model depends mainly on the features of available temperature data at a particular place. As a result, existing probability distributions must be evaluated to establish an appropriate probability model that can deliver precise temperature estimation. The study intended to estimate the best-fitted probability model for the monthly maximum temperature at the Sylhet station in Bangladesh from January 2002 to December 2012 using several statistical analyses. Ten continuous probability distributions such as Exponential, Gamma, Log-Gamma, Beta, Normal, Log-Normal, Erlang, Power Function, Rayleigh, and Weibull distributions were fitted for these tasks using the maximum likelihood technique. To determine the model’s fit to the temperature data, several goodness-of-fit tests were applied, including the Kolmogorov-Smirnov test, Anderson-Darling test, and Chi-square test. The Beta distribution is found to be the best-fitted probability distribution based on the largest overall score derived from three specified goodness-of-fit tests for the monthly maximum temperature data at the Sylhet station.

scholarly journals A best-fit probability distribution for the estimation of rainfall in northern regions of Pakistan

2016 ◽  
Vol 11 (1) ◽  
pp. 432-440 ◽  
Author(s):  
M. T. Amin ◽  
M. Rizwan ◽  
A. A. Alazba
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Future Research ◽  
Maximum Rainfall ◽  
Type Iii ◽  
Goodness Of Fit Tests ◽  
Pearson Type ◽  
Northern Regions ◽  
Best Fit

AbstractThis study was designed to find the best-fit probability distribution of annual maximum rainfall based on a twenty-four-hour sample in the northern regions of Pakistan using four probability distributions: normal, log-normal, log-Pearson type-III and Gumbel max. Based on the scores of goodness of fit tests, the normal distribution was found to be the best-fit probability distribution at the Mardan rainfall gauging station. The log-Pearson type-III distribution was found to be the best-fit probability distribution at the rest of the rainfall gauging stations. The maximum values of expected rainfall were calculated using the best-fit probability distributions and can be used by design engineers in future research.

scholarly journals Fit Adequacy of Dichotomous Logit Response Models of the Regressor Bernoulli and Binomial Probability Distributions

2016 ◽  
Vol 16 ◽  
pp. 38-48
Author(s):  
G. Uzodinma Ugwuanyim ◽  
Chukwudi Justin Ogbonna
Keyword(s):  
Goodness Of Fit ◽  
Probability Distributions ◽  
Probability Models ◽  
Response Models ◽  
Explanatory Variables ◽  
Fit Statistics ◽  
Binomial Distributions ◽  
Multiple Correlation Analysis ◽  
Work Done ◽  
Best Fit

Logit models belong to the class of probability models that determine discrete probabilities over a limited number of possible outcomes. They are often called ‘Quantal Variables’ or ‘Stimulus and Response Models’ in Biological Literature. The conventional R2 measure of goodness-of-fit is problematic in logit models. This has therefore led to the proposal of several alternative goodness-of-fit measures. But researchers in this area have identified the base rate problem in using these several alternative goodness-of-fit measures. This research is an extension of work done by people in this area. Specifically, this research is aimed at investigating the goodness-of-fit performances of eight statistics using the Bernoulli and Binomial distributions as explanatory variables under various scenarios. The study will draw conclusions on the “best” fit. The data for the study was generated through simulation and analysed using the multiple correlation analysis. The findings clearly show that for the Bernoulli Distribution, the goodness-of-fit statistics to use are: RO2, RC2, RM2 and λp; and for the Binomial Distribution, the goodness-of-fit statistics to use are: and RN2 and λp. RO2 stood out as the “best” goodness-of-fit statistics.

scholarly journals Investigation of the effect of climate change on heat waves

2020 ◽  
Vol 2 (1) ◽  
pp. 54-60 ◽  
Author(s):  
Safieh Javadinejad ◽  
◽  
Rebwar Dara ◽  
Forough Jafary ◽  
◽  
...  
Keyword(s):  
Heat Waves ◽  
Temperature Data ◽  
Maximum Temperature ◽  
Thermal Waves ◽  
Cmip5 Model ◽  
Base Period ◽  
Short Term ◽  
South Sea ◽  
Rcp 8.5 ◽  
Research Show

The purpose of this research is to identify the heat waves of the South Sea of Iran and compare the conditions in the present and future. To reach this goal, the average daily temperature of 35 years has been used. Also, in order to predict future heat waves, the maximum temperature data of four models of the CMIP5 model series, according to the RCP 8.5 scenario, has been used for the period 2040-2074. In order to reverse the output of the climatic models, artificial neural networks were used to identify the thermal waves, and the Fumiaki index was used to determine the thermal waves. Using the programming in MATLAB software, the days when their temperature exceeded 2 standard deviations as a thermal wave were identified. The results of the research show that the short-term heat waves are more likely to occur. Heat waves in the base period have a significant but poorly developed trend, so that the frequency has increased in recent years. In the period from 2040 to 2074, the frequency of thermal waves has a significant decreasing trend, but usually with low coefficients. However, for some stations from 2040 to 2074, the frequency of predicted heat waves increased.

scholarly journals Probability Distributions of Peanut Seed Size

1978 ◽  
Vol 5 (2) ◽  
pp. 91-96 ◽  
Author(s):  
James I. Davidson ◽  
Paul D. Blankenship ◽  
Victor Chew
Keyword(s):  
Experimental Data ◽  
Seed Size ◽  
Probability Distributions ◽  
Logistic Distribution ◽  
Agronomic Practices ◽  
Harvest Dates ◽  
Arachis Hypogaea L ◽  
Mathematical Relationships ◽  
Best Fit ◽  
Standard Probability

Abstract Procedures and mathematical relationships were developed to describe seed size distributions for Florigiant, Florunner, and Starr peanut (Arachis hypogaea L.) varieties. Of six standard probability distributions studied, the normal and logistic distributions provided the best fit for the experimental data, These two distributions were therefore fitted to seed size data for several lots of peanuts. For each lot both the normal and logistic distributions provided an excellent fit to the experimental data, but the logistic was slightly superior. Differences between experimental and calculated values were greatest for lots that were the least or most mature. A logistic distribution was also fitted to the average of all data for each variety. These relationships may be used to better relate seed size to quality, marketing, shelling, and processing. They will also be useful in research studies of the effects on seed size of such variables as variety, agronomic practices, climate, soil moisture, and harvest dates.

scholarly journals Distribution of Earthquake Magnitude Levels in Bangladesh

2019 ◽  
Vol 11 (3) ◽  
pp. 15
Author(s):  
Md. Habibur Rahman ◽  
Md. Moyazzem Hossain
Keyword(s):  
Probability Distribution ◽  
Normal Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Earthquake Magnitude ◽  
Human Beings ◽  
Richter Scale ◽  
Log Normal ◽  
Log Normal Distribution ◽  
Best Fit

Earthquakes are one of the main natural hazards which seriously make threats the life and property of human beings. Different probability distributions of the earthquake magnitude levels in Bangladesh are fitted. In terms of graphical assessment and goodness-of-fit criterion, the log-normal distribution is found to be the best fit probability distributions for the earthquake magnitude levels in Bangladesh among the probability distribution considered in this study. The average earthquake magnitude level found 4.67 (in Richter scale) for log-normal distribution and the approximately forty-six percent chance is predicted to take place earthquake magnitude in the interval four to five.

scholarly journals Selecting the probability distribution of annual maximum temperature in Malaysia

2021 ◽  
Vol 36 ◽  
pp. 01010
Author(s):  
Nurfatini Mohd Supian ◽  
Husna Hasan
Keyword(s):  
Probability Distribution ◽  
Goodness Of Fit ◽  
Agricultural Sector ◽  
Estimation Method ◽  
Information Criterion ◽  
Maximum Temperature ◽  
Logistic Distribution ◽  
Annual Maximum ◽  
Goodness Of Fit Test ◽  
Annual Maximum Temperature

The issues on global warming have become very popular and been discussed both locally and internationally. This phenomenon due to the temperature rises will increase the variability of climate and more natural disasters were expected to occur. Increasing of global temperature will affect the agricultural sector, increase some of the infectious diseases that may lead to high mortality rates in humans, high demand for electricity, water and food which eventually affecting the economy of Malaysia. Hence, this work aims to study the best fitted probability distribution that describes the annual maximum temperature recorded at seventeen meteorological stations in Malaysia. The Normal, Lognormal, Gamma, Weibull and Generalized Skew Logistic distributions are considered using the maximum likelihood estimation method to estimate the parameters. The goodness of fit test and model selection criteria such as Kolmogorov-Smirnov and AndersonDarling tests, Corrected Akaike Information Criterion and Bayesian Information Criterion are used to measure the accuracy of the predicted data using theoretical probability distributions. The results show that most of the stations favour the Generalized Skew Logistic distribution as the best fitted probability distribution. Also, some stations favour the Normal, Lognormal as well as Weibull distribution as the best fitted distribution to describe the annual maximum temperature.

Prediction of Haemoglobin Level by Some Probability Distribution

2020 ◽  
Vol 9 (1) ◽  
pp. 84-88
Author(s):  
Govinda Prasad Dhungana ◽  
Laxmi Prasad Sapkota
Keyword(s):  
Probability Distribution ◽  
Normal Distribution ◽  
Goodness Of Fit ◽  
Continuous Variable ◽  
Hemoglobin Level ◽  
Chi Square ◽  
Chi Square Test ◽  
Log Normal ◽  
Two Parameters ◽  
Best Fit

 Hemoglobin level is a continuous variable. So, it follows some theoretical probability distribution Normal, Log-normal, Gamma and Weibull distribution having two parameters. There is low variation in observed and expected frequency of Normal distribution in bar diagram. Similarly, calculated value of chi-square test (goodness of fit) is observed which is lower in Normal distribution. Furthermore, plot of PDFof Normal distribution covers larger area of histogram than all of other distribution. Hence Normal distribution is the best fit to predict the hemoglobin level in future.

scholarly journals The Effect of the Thermal Mass of the Building Envelope on Summer Overheating of Dwellings in a Temperate Climate

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4117
Author(s):  
Tadeusz Kuczyński ◽  
Anna Staszczuk ◽  
Piotr Ziembicki ◽  
Anna Paluszak
Keyword(s):  
Building Materials ◽  
Heat Waves ◽  
Residential Buildings ◽  
Building Envelope ◽  
Temperate Climate ◽  
Maximum Temperature ◽  
Thermal Mass ◽  
Occupant Behavior ◽  
Average Maximum ◽  
Night Ventilation

The main objective of this paper is to demonstrate the effectiveness of increasing the thermal capacity of a residential building by using traditional building materials to reduce the risk of its excessive overheating during intense heat waves in a temperate climate. An additional objective is to show that the use of this single passive measure significantly reduces the risk of overheating in daytime rooms, but also, though to a much lesser extent, in bedrooms. Increasing the thermal mass of the room from light to a medium heavy reduced the average maximum daily temperature by 2.2K during the first heat wave and by 2.6K during the other two heat waves. The use of very heavy construction further reduced the average maximum temperature for the heat waves analyzed by 1.4K, 1.2K and 1.7K, respectively, giving a total possible reduction in maximum daily temperatures in the range of 3.6 °C, 3.8 °C and 4.3 °C. A discussion of the influence of occupant behavior on the use of night ventilation and external blinds was carried out, finding a significant effect on the effectiveness of the use of both methods. The results of the study suggest that in temperate European countries, preserving residential construction methods with heavy envelopes and partitions could significantly reduce the risk of overheating in residential buildings over the next few decades, without the need for night ventilation or external blinds, whose effectiveness is highly dependent on individual occupant behavior.

Sign in / Sign up

Export Citation Format

Share Document