That research also uses global ridge regression as a weight estimation method. The dominance of RBFNN model was also reported by [3] and [12]. It is used by adding the single positive regulatory parameter λ to the Sum Square Error (SSE), so that the function to be minimized is written in the following equation. 5) The optimal weight vector produced by global ridge regression method is.
Discussion
While the number of clusters ideally depends on those three other aspects. So, the best RBFNN model is model with Gaussian activation function, 19 clusters and proportion training test data 75%-25%, which is estimated by global ridge regression method. The architecture of the best RBFNN model is model with inputs 𝑥𝑡−1, 𝑥𝑡−2, 𝑥𝑡−3, 𝑥𝑡−4and 𝑥𝑡−5, 19 single output neurons and 1 bias on the hidden neurons.
Conclusion
Estimating The Break-Point of Segmented Simple Linear Regression using Empirical Likelihood Method
Introduction
Literature Review
- The Segmented Simple Linear Regression
- The Empirical Likelihood
Set the value of E Yi when Xi n, then adjust the regression model in each segment so that it continues at the breakpoints. We do not need the data to follow some parametric distribution in order to construct the empirical likelihood function.
1log
The Empirical Likelihood Ratio
If the value of R F is so small that it is less than the critical value of the distribution of X, then the ratio of X having an expected value E X is small.
Estimating the Break-point of Segmented Simple Linear Regression
- Estimating one Break-point
1log1
Estimating N Break-point
The single breakpoint estimation algorithm can be used to determine whether there are more than breakpoints. An identical algorithm can be used to detect the breakpoint on the cluster Xi,Yi nik*1.
Case Study
- Data
- Segmented Simple Linear Regression with One Break-point
- Segmented Simple Linear Regression with More Than One Break-point
- Discussion
We can say that the segmented regression model with 1 breakpoint is better than the usual simple regression model. We could see that the segmented regression model with one breakpoint has the lowest SSE.
Conclusion
Therefore, we can say that the segmented regression model with one breakpoint is the best model among the three for the chlorine data. It is better if we can detect more than one breakpoint at the same time.
Risk Factor of Formaldehyde Detection on Sales Location of Jambal Rotisalted Fish (Arius Thalassinus) in Yogyakarta
This research calculates the concentration of formaldehyde in fish muscles using TCA extraction and Nash reagent. The purpose of this research is the detection of formaldehyde in fish and shellfish using nass's reagent and TCA.
Riaz Uddin et al, 2011 Detection of formalin in fish samples collected in Dhaka City, Bangladesh. Castell and Barbara Smith, 1972 Measurement of formaldehyde in fish muscles using TCA extraction and the Nash reagent.
Qualitative detection of formalin detection kit for fish developed by Bangladesh Council of Scientific and Industrial Research (BCSIR). Noordiana N et al, 2011 Formaldehyde content and quality characteristic of selected fish and seafood from wet markets.
Material & Methodology
- Data
- Method
- Schiff solution
- Sample Detection
- Data analysis
Two drops of concentrated HCl were added to the salted fish extract. Positive samples were determined when the color remained purple, otherwise negative. A., "RISK FACTOR OF DETECTION OF FORMALDEHYDE AT THE POINT OF SALE OF SALT ROTI FISH (Arius Thalassinus) IN YOGYAKARTA".
Results and Discussion
- Result
- Discussion
Descriptive analysis in Figure 1, 2 and Table 1 showed that samples of salted fish yambal roti coming from traditional markets were formaldehyde positive detected and samples were negative. But no statistically significant relationship between the location of sale and the detection of formaldehyde in salted fish yambal roti (pvalue > 0.05).
Cluster Analysis and Its Various Problems
Material & Methodology
The three applications of distance measurements in this study were also performed using the bootstrap method to see consistency in determining the best distance measurement. Cophenetic correlation coefficient was used to determine the best distance measurement of the hierarchical clustering method, and the criteria used to evaluate the clustering results of the k-means algorithm is coefficient silhouette.
Literature Review
- Distance Measurement Autocorrelation Distance
- Cluster Analysis Hierarchical Method
This approach was performed by fitting the time series sample to a straight line. Dynamic Time Warping (DTW) is an algorithm for calculating the distance between two time series by determining the optimal warping path.
Volatility Modelling Using Hybrid Autoregressive Conditional Heteroskedasticity (ARCH) -Support Vector Regression (SVR)
- Autoregressive Conditional Heteroskedasticity (ARCH)
- Support Vector Regression (SVR)
- Kernel Function
- Selection Parameters
- Hybrid ARCH-SVR
- Value atRisk(VaR)
- Result
- Determination of Kernel function and parameters for hyperplane
- Calculation of VaR using the best model
The best parameters of the kernel function are determined by sampling some of the values in a specific range to build the hyperplane. While the results of the predictive value of the stock return volatility can be seen in Figure 2.
Optimization of Fuzzy System Using Point Operation Intensity Adjustment for Diagnosing Breast Cancer
The Modeling Process
After the data is extracted, the data is classified by becoming 80% training data and 20% test data. System testing is done by determining the accuracy base on true data and false data.
Results and Discussion
The domain value and curve width are different. The output is defined by representing a combination of a triangular curve and a trapezoidal curve. Equation (2) used to determine the membership rate. The selected maximum value, which is the basic union operating function [8] used, as shown in equation (3).
Conclusion
From Table 2, the accuracy values of fuzzy system without point operation are 94.79% for training data and 50% for testing data. The accuracy of the fuzzy system with the adjustment of the intensity of operation at points are analogous and the value is 96.875% for the training data and 91.67% for the test data.
Appendix
Thurston Method, Area Development Project Impact Evaluation in Pasaman Barat
Integrated Regional Rural Development of West Pasaman
Consequently, the relative importance of the factors contributing to the changes in the West Pasaman score is presented in Table 1. As expected, the method presented in this paper can be used to measure the relative importance of the four projects developed in West Pasaman.
Simulation Study of Robust Regression in High Dimensional Data Through the LAD-LASSO
LAD-LASSO
Then the LASSO formula was modified by Fan and Li 2001 [4] to avoid the bias. As can be seen, the LAD-𝐿𝐴𝑆𝑆𝑂 criterion combines the LAD criterion and the lasso penalty, and therefore the resulting estimator is expected to be strong against outliers and also enjoy a sparse representation.
Simulation Study
A., “A simulation study of robust regression in high-dimensional data via LAD-LASSO”. where 𝜆 > 0 is the tuning parameter. Robust regression shrinkage and consistent variable selection through LAD-lasso”, JBES ace in variable selection via nonconcave penalized likelihood and its Oracle properties,” Journal of the American Statistical Association.
An Implementation of Genetic Algorithm to Generate the Most Compromised Decision when Information of the Alternativesis
Incomplete
Basic Notation and Problem Definition
An implementation of the genetic algorithm to generate the most compromised decision when the information of the alternative. S., "An implementation of the genetic algorithm to generate the most compromised decision when the information of the alternatives is incomplete".
Proposed Approach
The basic idea of the approach is that the preference ranking vector should have high matching with the criteria. Assume that Rk is the correlation between criterion k and the preference rank vector s, or Rk = corr(zk, s).
Illustrative Example
To compare how good the result of the proposed algorithm is, we performed 2000 repetitions of random permutation. We could see that the best result with this procedure is about 0.713, which is worse than the one we obtained with a genetic algorithm.
Estimation of MedianGrowth Charts for Children Based on Biresponse Semiparametric Regression Model
Related Works/Literature Review
We then analyzed the 50th percentiles to assess the median growth chart of children based on bi-response semiparametric regression where the response variables, i.e., weight (kg) and height (cm), while a parametric predictor variable is gender and a non-parametric predictor variable is age (month). M., "Estimation of median growth curves for children based on bi-response semiparametric regression model using local linear estimator".
18)with
Then we assessed the median growth chart of weight-for-age and height-for-age for boys and girls. The median growth chart of weight-for-age and height-for-age for boys was higher than girls.
Feature Reduction of Wayang Golek Dance Data Using Principal Component Analysis (Pca)
- Motion Capture (mocap) Technique
- Sensor Kinect
- Principal component Analysis (PCA)
- The Principal Component Analysis Based Formed Covariance Matrix
- The Principal Component Analysis Based Formed Correlation Matrix
- Material & Method
- Reference
Kinect sensor motion capture (mocap) is Biovision Hierarchy (BVH) movement data of Wayang Golek Menak Yogyakarta dancers. Kinect sensor motion capture (mocap) results are Biovision Hierarchy (BVH) movement data of Wayang Golek Menak Yogyakarta dancers.
The Ability The Chi Squares StatisticsTo Rejecting The Null Hypothesis on Contingency Tables 2x2
Contingency Table 2x2 Analysis
Nugraha, Jaka., "The Ability of the Chi-Square Statistics to Reject the Null Hypothesis on 2x2 Contingency Tables". If an expected frequency is lower than five, you have alternatives: Yates correction (Yates' Chi-square test) and the N - 1 chi-square test.
Calculation ofMinimumSamples Size
The Yates correction (Yates, 1934) is equivalent to Pearson's chi-square, but with a continuity correction. In cases where the expected frequency is below 5, the Yates correction brings the result more in line with the true probability. Campbell (2007) conducted a very extensive sampling study on 2x2 tables comparing different chi-square statistics under different sample sizes and different baseline designs.
Properties of Functions F(K; ;X)
In general, Yates' statistics require larger sample sizes than probability statistics, Campbell's statistics, and Pearson's statistics to be able to detect individual differences. In more detail, to determine the statistical differences the probability statistics, Campbell's statistics and Pearson's statistics took short intervals.
Predictive Simulation of Amount of Claims with Zero Truncated Negative Binomial Distribution
Modeling of the Claims
- Modeling of Frequency
- Modeling of Amount of Claims
Determining the amount of the claim requires modeling that includes elements of the frequency or number of visits used by health services, and a large proportion of the cost for each visit. So the modeling of the claims is multiplying frequency models by the cost model (quantity of claims model). FPM) and a comparison of these models can be seen in Duan, et.all[2].
Amount of Claims Prediction with ZTNB
Modeling the claims is modeling based on the frequency of claims, assuming a negative binomial distribution. From the results of the test, by removing extreme data, a p-value = 0.072 was obtained, which states that the data frequency of claims follows the negative binomial distribution.
Deterministic and Probabilistic Seismic Hazard Risk Analysis in Bantul Regency
Maulina Supriyaningsih 1 , and Atina Ahdika 1
- Material & Methodology 1 Data
- Ground Motion Model (Attenuation Relationship)
- The Probabilistics Calculation
- Results and Discussion 1 Result
In [6], Lin & Lee (2008) studied about the ground motion attenuation characteristics of subduction zone earthquakes occurring in northeastern Taiwan. 6] Lin, P.-S., dan Lee, C.-T., "Ground Motion Attenuation Relationships for Subduction Zone Earthquakes in Northeast Taiwan", Bulletin of the Seismological Society of America.
![Figure 1. Seismic Source Zone for Indonesia Region [4]](https://thumb-ap.123doks.com/thumbv2/123dok/9201104.0/85.893.212.750.110.481/figure-seismic-source-zone-indonesia-region.webp)
Applying Extrapolation Technique to Flexible Binomial Model for Efficiency of American Option Valuation
- Related Work
- Flexible Binomial Model
- Repeated Richardson Extrapolation
- Repeated Richardson Ekstrapolation on Flexibel Binomial Model
- Numerical Result
- Conclusion
- Future Works
- Acknowledgement
- Reference
Primandari, A.H., Brilliant, I.H., "Application of the Extrapolation Technique to the Flexible Binomial Model for the Valuation Efficiency of American Options". The flexible binomial model with Richardson extrapolation is done by taking 100 initial time steps and 5 iterations.
Small Area Estimation Considering Skewness Data and Spatially Correlated Random Area Effects
A Brief of Empirical Best Linear Unbiased Predictor, Spatial Empirical Best Linear Unbiased Predictor and Empirical Best Prediction
In the standard SAE method, parameter estimation is based on a linear mixed model, which assumes that the variable of interest follows a normal distribution and that there is independence between small ranges.
Spatial Empirical Best Predictor (SEBP)
Final Remarks
This research tries to compare binary, uniform and kernel Gaussian W in SAR panel data model to get the best W based on RMSE value. Comparison of Binary, Uniform, and Kernel Gaussian Weight Matrix in Spatial Autoregressive (SAR) Panel Data Model and The.
Comparison of Binary, Uniform and Kernel Gaussian Weight Matrix in Spatial Autoregressive (SAR) Panel Data Model and The
The result is that Uniform W has the smallest RMSE value for almost all combinations of location number (n) and period number (t). So, if we run SAR-Panel Data Model, then it will be better if we use Uniform W to build correlation matrix. There are some types of W, they are Uniform W, Binary W, Inverse distance W and some W from real cases of economic conditions or transportation conditions from the area. This research aims to compare Binary W, Uniform W and Kernel Gaussian W in SAR panel data model using RMSE value obtained by simulation.
Application
- Related Works
- Rudimentary
- Data Panel Analysis
- Spatial Weighted Matrix (W)
- Spatial Autoregressive Panel Data Model (SAR-Panel Data) Autoregressive spatial models expressed in the following equation
- Material and Proposed Method
- Data
- Proposed Method
- Results and Discussion
Thus, it can be concluded that Uniform W is better than Binary and Kernel Gaussian W in SAR panel data model. In this study, the comparison of binary, uniform and kernel Gaussian weight matrix in Spatial Autoregressive (SAR) Panel Data Model has been presented.
Persistence Process of Stock Price Movements Based On Markov Chain Analysis
Data
Method
In addition, the state will be persistent if the initial state of the stock price is in the "jump down", "jump up" and "drastically up" states. In this paper, the stock price movement inertia index proposed in Proposition 1 was formulated.
Application of Fuzzy Logic to Diagnose Severity of Coronary Heart Disease: Case Study in dr. Zainoel Abidin General
Using Fuzzy Logic to Diagnose the Severity of Coronary Heart Disease: A Case Study Dr.
Hospital, Banda Aceh Indonesia
For the patients who have lower than normal level of the variables were excluded in this study. So we can check the diseases and risks in the patient according to the values of the variables.
Statistics Application On Terestrial Phenomena Of Metallic Mining’s Activity
Scale of Theory
- Resources and Reserves
- Error Tolerance and Level of Accuracy
- Geostatistics
- Variography
In statistical theory, the probability confidence level of a data distribution can be formulated by. The different confidence level values can be described by a normal distribution table and summarized in Table 4.
Reserves Estimate
- Characteristics of Ore
- Estimate Simulation
Limonite is the result of the weathering of soft yellowish-brown soil, which contains nickel and iron in an arbitrary ratio. Estimated reserves of nickel ore deposits are based on the data shown in Figure 2 and Table 5.
Discussion
In the future advantage, resources or reserves can be improved to increase the added value with optimal utilization. To reach the higher accuracy prediction of resources or reserves metallic deposits can be expressed with standard deviation value.
Empirical Study of Student’s Stage Thinking
According To Bloom And Van Hiele Learning Theories In Mathematics Instruction
Related works / literature review
In the learning process, there is an interaction which somehow involves the external matter of the student and the teacher, including the environment. The level of item difficulty in modern measurements is directly related to the feature of the item.
Material and method
The item number 20 in the Van Hiele's classification has a lower difficulty than in the introductory level and item number 11, an item in the deduction level, has a lower difficulty than in the order level. In fact, there is the result of simulation in the form of student worksheets that can be analyzed using the IRT approach.
Conclusions
The simulation data analysis using the difficulty level of the real data has a weakness, that is, the simulation result is in the form of the difficulty level of the classical test theory so that the difficulty level data obtained is based on the respondents . ability. However, due to the limitation of the researcher's ability to use other programs to calculate the difficulty level of the worksheets result from the simulation, then the researcher only uses the data that exists in the form of the classical difficulty level.
Service Quality in Religious and Common Tourism
Methodology
SQA10 Trash cans are clean and sufficient SQA11 There is a special way to switch off SQA12 There is a safe children's playground. There were differences between the results of religious and general tourism for the most important service item, the least important service item and the minimum service gap.
Maximum Likelihood Estimation In Intervention Analysis Model Multy Input Step Function: the impact of sea highway policies on
The first modeling is to determine the hypothesized order of b, s, and r of the first intervention model. To determine the order of the first intervention, you can see the residual diagram in Figure 4.2 below.
Indonesia’s Province Segmentation Based On Flood Disaster Impact With Self Organizing Maps (Som) Algorithm
Introduction
There are some grouping methods like K Means, K Medoid, etc, but Indonesia's situation is unique, some islands have different (external) characteristics. It is very suitable to handle the flood case of Indonesia and the result can be combined with GIS mapping method.
Related Works
Material and Methodology
It is usually set to be the grid radius, decreasing each time step. Fifth step, each node found within the radius of the BMU calculated in step 4 is adjusted to make them more like the input vector with this formula.
Result
The characteristics are unique because the members of this group have a lower degree of damage to the healthy object if the flood occurs, but the highest number of casualties due to the dead and missing compared to the other members of the group. The characteristics of this group is a large number of damages and many settlements are in severe damage if floods occur.
The Utilization Density Functional Theory in Structure Determination And Hydrogen Storage
DensityFunctionalTheory
The energy of N electrons in an external potential Vext(r) is written as a function of the electron density 𝑛(𝑟). The total electronic energy E is said to be a function of the electron density, donated 𝐸𝑡𝑜𝑡[𝑛(𝑟) ], in the sense that for a given function 𝑛(𝑟), as written as below,. Kurniawan., "Utilization Density Functional Theory in Structure Determination and Hydrogen Storage Properties of Ca(BH4)2∙2NH3 Compounds".
Material
- Determination of structure
- Hydrogen storage properties
To better provide some insight into the hydrogen storage properties of the Ca(BH4) 2∙2NH3 crystal, further study concerns the complex structure of this octahedrally shaped compound with ionic Ca2+ as the center and surrounded by four BH4 − molecule in lateral position and two NH3 molecules in vertical position. In this case, the modeling of a good geometrical structure of the compound Ca(BH4)2∙2NH3 is a necessary condition to correctly understand the crystal structure of Ca(BH4)2∙2NH3, the lattice parameters and its properties as a deposition material hydrogen.
Statistical Analysis of the difference Absolut Neutrophil Count (ANC) in the level sepsis patients
Rizka Asdie 2
Diagnosis of the infection and the patient with sepsis is often difficult because of the often multiple and complex underlying disease. The basic standard of care and individual organ support management of the patient with severe sepsis are 4 factors: infection control, hemodynamic support, immunomodulatory interventions, and metabolic/endocrine support.
The subjects with the inclusion and exclusion criteria of sepsis were taken informed consent and examination of laboratory.
