MODELING OF LOCAL POLYNOMIAL KERNEL NONPARAMETRIC REGRESSION FOR COVID DAILY CASES IN SEMARANG CITY, INDONESIA

2021 ◽  
Vol 14 (2) ◽  
pp. 206-215
Author(s):  
Tiani Wahyu Utami ◽  
Aisyah Lahdji
Keyword(s):  
Nonparametric Regression ◽  
Cross Validation ◽  
Statistical Approach ◽  
Polynomial Kernel ◽  
Model Estimation ◽  
Optimal Bandwidth ◽  
Local Polynomial ◽  
Central Java ◽  
Kernel Approach

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which was recently discovered. Coronavirus disease is now a pandemic that occurs in many countries in the world, one of which is Indonesia. One of the cities in Indonesia that has found many COVID cases is Semarang city, located in Central Java. Data on cases of COVID patients in Semarang City which are measured daily do not form a certain distribution pattern. We can build a model with a flexible statistical approach without any assumptions that must be used, namely the nonparametric regression. The nonparametric regression in this research using Local Polynomial Kernel approach. Determination of the polynomial order and optimal bandwidth in Local Polynomial Kernel Regression modeling use the GCV (Generalized Cross Validation) method. The data used this research are data on the number of COVID patients daily cases in Semarang, Indonesia. Based on the results of the application of the COVID patient daily cases in Semarang City, the optimal bandwidth value is 0.86 and the polynomial order is 4 with the minimum GCV is 3179.568 so that the model estimation results the MSE is 2922.22 and the determination coefficient is 97%. The estimation results show the highest number of Corona in the Semarang City at the beginning of July 2020. After the corona case increased in July, while the corona case in August decreased.

scholarly journals Estimator Nadaraya-Watson dengan Pendekatan Cross Validation dan Generalized Cross Validation untuk Mengestimasi Produksi Jagung

2021 ◽  
Vol 3 (2) ◽  
pp. 85
Author(s):  
Febriolah Lamusu ◽  
Tedy Machmud ◽  
Resmawan Resmawan
Keyword(s):  
Cross Validation ◽  
Kernel Estimator ◽  
Mean Square ◽  
Corn Production ◽  
Optimal Bandwidth ◽  
Generalized Cross Validation ◽  
Huge Impact ◽  
Kernel Approach ◽  
Independent Variable ◽  
Two Parameter

<p>Nadaraya-Watson Estimator with kernel approach depends on two-parameter, those are kernel function and bandwidth choice. However, between the two of them, bandwidth choice gave a huge impact on the result of the estimation. By minimizing the value of Mean Square Error (MSE), Cross-Validation (CV) and Generalized Cross-Validation (GCV) gave the optimal bandwidth value. In this research, corn production was considered as the dependent variable, while the planted area, harvested area, and the fertilizer as the independent variable. The result of this research showed that Nadaraya-Watson Estimator with Generalized Cross-Validation gives a better corn production estimation with optimal bandwidth value 742392,2, with and  with MSE 202583,9.</p><p><strong>Keywords</strong>: kernel, estimator Nadaraya-Watson, cross validation, generalized cross validation.</p>

scholarly journals Regresi Nonparametrik dengan Pendekatan Deret Fourier pada Data Debit Air Sungai Citarum

2018 ◽  
Vol 4 (2) ◽  
pp. 75-82
Author(s):  
Intaniah Ratna Nur Wisisono ◽  
Ade Irma Nurwahidah ◽  
Yudhie Andriyana
Keyword(s):  
Fourier Series ◽  
Nonparametric Regression ◽  
River Discharge ◽  
Cross Validation ◽  
Least Square ◽  
Nonparametric Regression Model ◽  
Optimal Bandwidth ◽  
Ordinary Least Square ◽  
Calculation Results ◽  
Series Technique

River discharge is one of the factors that affect the occurrence of floods. It varies over time and hence we need to predict the flood risk. Since the plot of the data changes periodically showing a sines and cosines pattern, a nonparametric technique using Fourier series approach may be interesting to be applied. Fourier series can be estimated using OLS (Ordinary Least Square). In a Fourier series, nonparametric regression the level of subtlety of its function is determined by their bandwidth (K). Optimal bandwidth determined using the GCV (Generalized Cross Validation) method. From the calculation results, we have optimal bandwidth which is equal to 16 with R2 is 0.7295 which means that 72.95% of the total variance in the river discharge variable can be explained by the Fourier series nonparametric regression model. Comparing to a classical time series technique, ARIMA Box Jenkins, we obtained ARIMA (1,0,0) with RMSE 83.10 while using Fourier series approach generate a smaller RMSE 50.51.

Determination of the Number of Conserved Chromosomal Segments Between Species

Genetics ◽  
2001 ◽  
Vol 157 (3) ◽  
pp. 1387-1395 ◽  
Author(s):  
Sudhir Kumar ◽  
Sudhindra R Gadagkar ◽  
Alan Filipski ◽  
Xun Gu
Keyword(s):  
Statistical Approach ◽  
Common Ancestor ◽  
Chromosomal Rearrangements ◽  
Structural Similarity ◽  
The Other ◽  
Segment Length ◽  
Human Genomes ◽  
Genomic Divergence ◽  
Human And Mouse

AbstractGenomic divergence between species can be quantified in terms of the number of chromosomal rearrangements that have occurred in the respective genomes following their divergence from a common ancestor. These rearrangements disrupt the structural similarity between genomes, with each rearrangement producing additional, albeit shorter, conserved segments. Here we propose a simple statistical approach on the basis of the distribution of the number of markers in contiguous sets of autosomal markers (CSAMs) to estimate the number of conserved segments. CSAM identification requires information on the relative locations of orthologous markers in one genome and only the chromosome number on which each marker resides in the other genome. We propose a simple mathematical model that can account for the effect of the nonuniformity of the breakpoints and markers on the observed distribution of the number of markers in different conserved segments. Computer simulations show that the number of CSAMs increases linearly with the number of chromosomal rearrangements under a variety of conditions. Using the CSAM approach, the estimate of the number of conserved segments between human and mouse genomes is 529 ± 84, with a mean conserved segment length of 2.8 cM. This length is &lt;40% of that currently accepted for human and mouse genomes. This means that the mouse and human genomes have diverged at a rate of ∼1.15 rearrangements per million years. By contrast, mouse and rat are diverging at a rate of only ∼0.74 rearrangements per million years.

Proteometabolomic characterization of apical bud maturation in Pinus pinaster

2020 ◽  
Author(s):  
Luis Valledor ◽  
Sara Guerrero ◽  
Lara García-Campa ◽  
Mónica Meijón
Keyword(s):  
Pinus Pinaster ◽  
Ribosomal Proteins ◽  
Potential Role ◽  
Statistical Approach ◽  
Wood Quality ◽  
Growth Patterns ◽  
Future Scenario ◽  
Apical Bud

Abstract Bud maturation is a physiological process which implies a set of morphophysiological changes which lead to the transition of growth patterns from young to mature. This transition defines tree growth and architecture, and in consequence traits such as biomass production and wood quality. In Pinus pinaster, a conifer of great timber value, bud maturation is closely related to polycyclism (multiple growth periods per year). This process causes a lack of apical dominance, and consequently increased branching that reduces its timber quality and value. However, despite its importance, little is known about bud maturation. In this work, proteomics and metabolomics were employed to study apical and basal sections of young and mature buds in P. pinaster. Proteins and metabolites in samples were described and quantified using (n)UPLC-LTQ-Orbitrap. The datasets were analyzed employing an integrative statistical approach, which allowed the determination of the interactions between proteins and metabolites and the different bud sections and ages. Specific dynamics of proteins and metabolites such as HISTONE H3 and H4, RIBOSOMAL PROTEINS L15 and L12, CHAPERONIN TCP1, 14–3-3 protein gamma, gibberellins A1, A3, A8, strigolactones and ABA, involved in epigenetic regulation, proteome remodeling, hormonal signaling and abiotic stress pathways showed their potential role during bud maturation. Candidates and pathways were validated employing interaction databases and targeted transcriptomics. These results increase our understanding of the molecular processes behind bud maturation a key step towards improving timber production and natural pine forests management in a future scenario of climate change. However, further studies are necessary by using different P. pinaster populations that show contrasting wood quality and stress tolerance in order to generalize the results.

scholarly journals Method of determining the distance to the object by analyzing its image blur

Vestnik MGSU ◽  
2015 ◽  
pp. 140-151 ◽  
Author(s):  
Aleksey Alekseevich Loktev ◽  
Daniil Alekseevich Loktev
Keyword(s):  
Least Squares ◽  
Statistical Approach ◽  
Evaluation Method ◽  
Least Squares Method ◽  
Focal Length ◽  
Error Variance ◽  
Method Of Least Squares ◽  
Automated Control ◽  
Image Blur

In modern integrated monitoring systems and systems of automated control of technological processes there are several essential algorithms and procedures for obtaining primary information about an object and its behavior. The primary information is characteristics of static and moving objects: distance, speed, position in space etc. In order to obtain such information in the present work we proposed to use photos and video detectors that could provide the system with high-quality images of the object with high resolution. In the modern systems of video monitoring and automated control there are several ways of obtaining primary data on the behaviour and state of the studied objects: a multisensor approach (stereovision), building an image perspective, the use of fixed cameras and additional lighting of the object, and a special calibration of photo or video detector.In the present paper the authors develop a method of determining the distances to objects by analyzing a series of images using depth evaluation using defocusing. This method is based on the physical effect of the dependence of the determined distance to the object on the image from the focal length or aperture of the lens. When focusing the photodetector on the object at a certain distance, the other objects both closer and farther than a focal point, form a spot of blur depending on the distance to them in terms of images. Image blur of an object can be of different nature, it may be caused by the motion of the object or the detector, by the nature of the image boundaries of the object, by the object’s aggregate state, as well as by different settings of the photo-detector (focal length, shutter speed and aperture).When calculating the diameter of the blur spot it is assumed that blur at the point occurs equally in all directions. For more precise estimates of the geometrical parameters determination of the behavior and state of the object under study a statistical approach is used to determine the individual parameters and estimate their accuracy. A statistical approach is used to evaluate the deviation of the dependence of distance from the blur from different types of standard functions (logarithmic, exponential, linear). In the statistical approach the evaluation method of least squares and the method of least modules are included, as well as the Bayesian estimation, for which it is necessary to minimize the risks under different loss functions (quadratic, rectangular, linear) with known probability density (we consider normal, lognormal, Laplace, uniform distribution). As a result of the research it was established that the error variance of a function, the parameters of which are estimated using the least squares method, will be less than the error variance of the method of least modules, that is, the evaluation method of least squares is more stable. Also the errors’ estimation when using the method of least squares is unbiased, whereas the mathematical expectation when using the method of least modules is not zero, which indicates the displacement of error estimations. Therefore it is advisable to use the least squares method in the determination of the parameters of the function.In order to smooth out the possible outliers we use the Kalman filter to process the results of the initial observations and evaluation analysis, the method of least squares and the method of least three standard modules for the functions after applying the filter with different coefficients.

scholarly journals A Statistical Approach to Model the H-Index Based on the Total Number of Citations and the Duration from the Publishing of the First Article

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Mohammad Reza Mahmoudi ◽  
Marzieh Rahmati ◽  
Zulkefli Mansor ◽  
Amirhosein Mosavi ◽  
Shahab S. Band
Keyword(s):  
Nonlinear Regression ◽  
Research Funding ◽  
Statistical Approach ◽  
Practical Approach ◽  
H Index ◽  
Model Based ◽  
Funding Agencies ◽  
Number Of Citations ◽  
The Impact

The productivity of researchers and the impact of the work they do are a preoccupation of universities, research funding agencies, and sometimes even researchers themselves. The h-index (h) is the most popular of different metrics to measure these activities. This research deals with presenting a practical approach to model the h-index based on the total number of citations (NC) and the duration from the publishing of the first article (D1). To determine the effect of every factor (NC and D1) on h, we applied a set of simple nonlinear regression. The results indicated that both NC and D1 had a significant effect on h ( p  < 0.001). The determination of coefficient for these equations to estimate the h-index was 93.4% and 39.8%, respectively, which verified that the model based on NC had a better fit. Then, to record the simultaneous effects of NC and D1 on h, multiple nonlinear regression was applied. The results indicated that NC and D1 had a significant effect on h ( p  < 0.001). Also, the determination of coefficient for this equation to estimate h was 93.6%. Finally, to model and estimate the h-index, as a function of NC and D1, multiple nonlinear quartile regression was used. The goodness of the fitted model was also assessed.

scholarly journals Determination of Scandium in mafic and ultramafic rocks of ophiolites from Luk Ulo Complex, Karangsambung, Central Java, Indonesia

2020 ◽  
Vol 200 ◽  
pp. 06003
Author(s):  
Nugroho Imam Setiawan ◽  
Kardo Polarman Rajoki Silitonga ◽  
Fahmi Adiyatma Makkaratte ◽  
Chusni Ansori
Keyword(s):  
Mineral Composition ◽  
General Trend ◽  
Elemental Abundance ◽  
Ultramafic Rocks ◽  
Mining Activities ◽  
Central Java ◽  
Parent Rocks ◽  
Modern Industry

Scandium (Sc) is important element for its utilization in modern industry. Initial Sc content in the parent rocks primary importance controlling the Sc concentrations in its weathered derivatives. This contribution examines the Sc concentrations in parent rocks of mafic and ultramafic rocks related to the ophiolite series in Luk Ulo Complex, Karangsambung, Central Java, Indonesia. The ophiolite series in this area are basalt, microgabbronorite, gabbronorite, websterite, and serpentinite from 5 locations of Medana, Lokidang, Parakansubah, Selogiri, and Pucangan areas. The general trend from the distribution of Sc in the ophiolite sequence of Medana and Parakansubah-Lokidang Rivers suggests the Sc contents increase from shallow to deeper levels of the sequence. The lowest concentrations of Sc in the ophiolite sequence of Medana and Parakansubah-Lokidang Rivers are in basalt, which are 24–29 ppm. In the middle sequence, the Sc concentrations are 27–34 ppm and 24–43 ppm, respectively in microgabbronorite and gabbronorite. The highest Sc concentrations are in websterite, which are 51–54 ppm, as the deepest sequence of the ophiolite in this area. Meanwhile, Sc contents in serpentinite from Selogiri and Pucangan areas are 5–11 ppm, which are considered the lowest Sc contents. It suggests that the pre-serpentinization mineral composition rather than the process of serpentinization determine the elemental abundance of Sc in serpentinite. The results are used to be an analog for Sc identification in the ophiolite belts in central Indonesia. This also considering that Luk Ulo Complex been established as National Geopark of Karangsambung-Karangbolong, so that mining activities are prohibited in this area.

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