scholarly journals Behaviour of spatial rainfall correlation For short distances

MAUSAM ◽  
2021 ◽  
Vol 43 (3) ◽  
pp. 269-272
Author(s):  
J. N. KANAUJIA ◽  
SURINDER KAUR ◽  
D. S. Upadhyay
Keyword(s):  
Theoretical Model ◽  
Missing Data ◽  
Network Design ◽  
Short Distance ◽  
Annual Rainfall ◽  
Parameter Distribution ◽  
Data Interpolation ◽  
Areal Rainfall ◽  
Transfer Of Information ◽  
Two Parameter

The correlation between two series of rainfall recorded at two stations which are at short distance, is usually found significant. This information has important applicability in the areas of data interpolation, network design, transfer of information in respect of missing data and deriving areal rainfall from point values. In this paper 70-year (1901-1970) annual rainfall data for about 1500 stations in India have been analysed. The distribution of correlation coefficient (r) for the stations located within a distance of 40 km were obtained. Attempt has been made to derive theoretical model of r. For this purpose two distributions, (1) a two parameter -distribution and (2) a two parameter bounded distribution, have been chosen as in both cases the variable ranges from 0 to 1.  

scholarly journals A Semi-Theoretical Model for Water Condensation: Dew Used in Conservation of Earthen Heritage Sites

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 52
Author(s):  
Xiang He ◽  
Sijia Wang ◽  
Bingjian Zhang
Keyword(s):  
Mass Transfer ◽  
Theoretical Model ◽  
Field Experiments ◽  
Environmental Control ◽  
Mass Transfer Process ◽  
Formation Processes ◽  
Heritage Sites ◽  
Dew Formation ◽  
The Difference ◽  
Two Parameter

Dew is a common but important phenomenon. Though water is previously considered to be a threat to earthen heritage sites, artificial dew is showing potential in relic preservation. A model of dew prediction on earthen sites will be essential for developing preventive protection methods, but studies of dew formation processes on relics are limited. In this study, a two parameter model is proposed. It makes approximations according to the features of earthen heritage sites, assuming that a thin and steady air layer exists close to the air–solid interface. This semi-theoretical model was based on calculations of the mass transfer process in the air layer, and was validated by simulations of laboratory experiments (R > 0.9) as well as field experiments. Additionally, a numerical simulation, performed by the commercial software COMSOL, confirmed that the difference between fitting parameter δ and the thickness of assumed mass transfer field was not significant. This model will be helpful in developing automatic environmental control systems for stabilizing water and soluble salts, thus enhancing preventive protection of earthen heritage sites.

scholarly journals CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use

2015 ◽  
Vol 8 (1) ◽  
pp. 83-112 ◽  
Author(s):  
V. D. J. Keller ◽  
M. Tanguy ◽  
I. Prosdocimi ◽  
J. A. Terry ◽  
O. Hitt ◽  
...  
Keyword(s):  
Monthly Rainfall ◽  
Annual Rainfall ◽  
National Database ◽  
Maximum Information ◽  
Weather Observations ◽  
The Republic ◽  
Areal Rainfall ◽  
The Uk ◽  
Rainfall Estimates

Abstract. The Centre for Ecology & Hydrology – Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset was developed to provide reliable 1 km gridded estimates of daily and monthly rainfall for Great Britain (GB) and Northern Ireland (NI) (together with approximately 3500 km2 of catchment in the Republic of Ireland) from 1890 onwards. The dataset was primarily required to support hydrological modelling. The rainfall estimates are derived from the Met Office collated historical weather observations for the UK which include a national database of raingauge observations. The natural neighbour interpolation methodology, including a normalisation step based on average annual rainfall, was used to generate the daily and monthly rainfall grids. To derive the monthly estimates, rainfall totals from monthly and daily (when complete month available) read raingauges were used in order to obtain maximum information from the raingauge network. The daily grids were adjusted so that the monthly grids are fully consistent with the daily grids. The CEH-GEAR dataset was developed according to the guidance provided by the British Standards Institution. The CEH-GEAR dataset contains 1 km grids of daily and monthly rainfall estimates for GB and NI for the period 1890–2012. For each day and month, CEH-GEAR includes a secondary grid of distance to the nearest operational raingauge. This may be used as an indicator of the quality of the estimates. When this distance is greater than 100 km, the estimates are not calculated due to high uncertainty. CEH-GEAR is available free of charge for commercial and non-commercial use subject to licensing terms and conditions. doi:10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e

Gibbs Sampling Method in the Multidimensional Logistic Response Model with Missing Responses

2014 ◽  
Vol 926-930 ◽  
pp. 3830-3833
Author(s):  
Zhi Hui Fu ◽  
Cui Xin Peng ◽  
Bin Li
Keyword(s):  
Missing Data ◽  
Logistic Model ◽  
Sampling Method ◽  
Missing Values ◽  
Data Augmentation ◽  
Posterior Distributions ◽  
Missing Responses ◽  
Bayesian Paradigm ◽  
Item Parameters ◽  
Two Parameter

Missing data are often a problem in statistical modeling. How to estimate item parameters with missing data in item response theory (IRT) is an interesting issue. The Bayesian paradigm offers a natural model-based solution for this problem by treating missing values as random variables and estimating their posterior distributions. In this article, based on a data augmentation scheme using the Gibbs sampler, we propose a Bayesian procedure to estimate the multidimensional two parameter Logistic model with missing responses.

scholarly journals A New Extended Two-Parameter Distribution: Properties, Estimation Methods, and Applications in Medicine and Geology

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1578 ◽  
Author(s):  
Hazem Al-Mofleh ◽  
Ahmed Z. Afify ◽  
Noor Akma Ibrahim
Keyword(s):  
Estimation Method ◽  
Estimation Methods ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Unknown Parameters ◽  
Proposed Model ◽  
Rate Functions ◽  
The Mean ◽  
Modeling Data ◽  
Two Parameter

In this paper, a new two-parameter generalized Ramos–Louzada distribution is proposed. The proposed model provides more flexibility in modeling data with increasing, decreasing, J-shaped, and reversed-J shaped hazard rate functions. Several statistical properties of the model were derived. The unknown parameters of the new distribution were explored using eight frequentist estimation approaches. These approaches are important for developing guidelines to choose the best method of estimation for the model parameters, which would be of great interest to practitioners and applied statisticians. Detailed numerical simulations are presented to examine the bias and the mean square error of the proposed estimators. The best estimation method and ordering performance of the estimators were determined using the partial and overall ranks of all estimation methods for various parameter combinations. The performance of the proposed distribution is illustrated using two real datasets from the fields of medicine and geology, and both datasets show that the new model is more appropriate as compared to the Marshall–Olkin exponential, exponentiated exponential, beta exponential, gamma, Poisson–Lomax, Lindley geometric, generalized Lindley, and Lindley distributions, among others.

scholarly journals Modelling the COVID-19 Mortality Rate with a New Versatile Modification of the Log-Logistic Distribution

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Abdisalam Hassan Muse ◽  
Ahlam H. Tolba ◽  
Eman Fayad ◽  
Ola A. Abu Ali ◽  
M. Nagy ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Goodness Of Fit ◽  
Likelihood Estimation ◽  
Cumulative Distribution ◽  
Logistic Distribution ◽  
Parameter Distribution ◽  
Unknown Parameters ◽  
Failure Rate Function ◽  
Competing Models ◽  
Two Parameter

The goal of this paper is to develop an optimal statistical model to analyze COVID-19 data in order to model and analyze the COVID-19 mortality rates in Somalia. Combining the log-logistic distribution and the tangent function yields the flexible extension log-logistic tangent (LLT) distribution, a new two-parameter distribution. This new distribution has a number of excellent statistical and mathematical properties, including a simple failure rate function, reliability function, and cumulative distribution function. Maximum likelihood estimation (MLE) is used to estimate the unknown parameters of the proposed distribution. A numerical and visual result of the Monte Carlo simulation is obtained to evaluate the use of the MLE method. In addition, the LLT model is compared to the well-known two-parameter, three-parameter, and four-parameter competitors. Gompertz, log-logistic, kappa, exponentiated log-logistic, Marshall–Olkin log-logistic, Kumaraswamy log-logistic, and beta log-logistic are among the competing models. Different goodness-of-fit measures are used to determine whether the LLT distribution is more useful than the competing models in COVID-19 data of mortality rate analysis.

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