Quinn Information Criterion Research Articles

Exponentiated Inverse Chen distribution: Properties and applications

A new distribution having three parameters called Exponentiated Inverse Chen distribution is proposed in this study. Important statistical properties like Survival function, hazard rate function, skewness and kurtosis etc are studied. Some methods of estimation Least Square, Maximum likelihood and Cramer-Von Mises methods are used using R programming software. A data set is discussed and Validity of the model is tested by analyzing P-P and Q-Q plots. Different information criteria such as Akanke’s information criterion, Bayesian information criterion, Corrected Akanke’s information criterion, and Hannan – Quinn information criterion are applied for model comparisons. For testing the goodness of fit of the proposed model, Kolmogrov-Smirnov, Anderson darling and Cramer –Von Mises statistics are used. The proposed model called Exponentiated Inverse Chen distribution is more applicable as compared to some existing probability model. It is found that MLEs are better with respect to LSE and CVM. PDF curve of model has shown that it can have various shapes like increasing as well as decreasing, monotonically increasing, constant as well as inverted bathtub shaped based hazard function is seen. Applicability and suitability of model is evaluated. For this, we have considered a real-life dataset. We found distribution that EIC is much flexible.

Estimation of the Xrama Distribution Parameter Under Complete and Progressive Type-II Censored Schemes

In this paper, a two-component mixture of Exponential and Rama distribution named Xrama distribution is introduced and discussed. The distributional properties such as moment and the related measures including other characteristics namely quantile function, mean residual life function, Bonferroni curve, Lorenz curve, order statistics, stochastic ordering, and entropy were derived. Simulation study for both complete and progressive type-2 censored schemes is used to illustrate and analyze the behavior of the model. The proposed model’s performance is assessed through a comparison with various other lifetime distributions using negative log-likelihood, Akaike Information Criterion, Corrected Akaike Information Criterion, Bayesian Information Criterion, and Hannan–Quinn information criterion on an actual dataset. The results reveal that, when modeling real lifetime data, the suggested model exhibits greater flexibility than the competing models examined in this study.

A new extension of linear failure rate distribution with estimation, simulation, and applications

In this article, we provide a new three-parameter model derived from the newly reduced Cauchy power-G family and linked to the linear failure rate model. The truncated Cauchy power linear failure rate (TCPLFR) is the name given to this distribution. The TCPLFR distribution also contains the truncated Cauchy power Rayleigh distribution and the truncated Cauchy power exponential distribution as sub-models. The TCPLFR distribution has rising, falling, and U-shaped hazard rate functions. The distribution characteristics of the TCPLFR are presented. To compute the population parameters’ point and estimated confidence intervals, the maximum likelihood approach is employed. We explore the behavior of the maximum likelihood estimates as well as the estimated confidence intervals for the model parameters using Monte Carlo simulation. To demonstrate the significance and flexibility of the TCPLFR distribution, the Akaike information criterion (D1), Bayesian information criterion (D2), consistent Akaike information criterion (D3), Hannan–Quinn information criterion (D4), and Kolmogorov–Smirnov (D5) statistic with its p-value (D6) were employed. According to a real-world data analysis, the truncated Cauchy power linear failure rate distribution outperforms alternative models with two, three, and four parameters.

What Influenced Hanoi’s Apartment Price Bubble between 2010 and 2021?

This study focused on testing the existence of an apartment price bubble in Hanoi (Vietnam) and on determining the factors that affected it in the period between 2010 and 2021. Using the fundamental factor approach, the authors applied VAR regression using time series data. Specifically, we used the ADF unit test to test the stationarity of the variables based on the following criteria: AIC (Akaike information criterion); LR (likelihood ratio); FPE (final prediction error); HQ (Hanan–Quinn information criterion); and Schwarz (SC) to find the optimal lag (Lag) for the model. We also applied the Granger causality test to determine the correlation between the economic variables that appeared in the model with the PR index. We present the results of the research model through the push–response function and the variance decomposition to consider and evaluate the impact of the PR index shock on itself and the other variables. The literature in this field includes many studies that are similar to this one; however, no research has been conducted that has focused on analysing whether variables, such as per capita income and the urbanisation rate, influence the formation of real estate bubbles. This focus is especially relevant in Hanoi, which is an important part of the Vietnamese real estate market. Through this study, we aimed to fill this gap and to contribute to the references on the Hanoi real estate market and its influencing factors.

Comparison between the Four-parameter and Five-parameter Logistics Equations in the Determination of the Limits of Detection of Ochratoxin A

Ochratoxin A, a type of mycotoxin, was detected in plant sample matrices using the "optical waveguide lightmode spectroscopy" (OWLS) method. The calibration curve for the detection of ochratoxin A utilizing "optical waveguide lightmode spectroscopy" (OWLS) displayed a sigmoidal shape; hence, the 5-parameter logistics (5-PL) or 4-parameters logistics (4-PL) model should be used to fit the data rather than a linear model. Through the use of error function analysis and various functions such as Bias Factor, corrected Akaike Information Criterion (AICc), adjusted correlation coefficient (adjR2), Hannan–Quinn information criterion (HQC), Root Mean Square Error (RMSE), Bayesian Information Criterion (BIC), and Accuracy Factor, the distinction between the 5-PL and 4-PL models is found to be inconsistent. The half maximal effective concentration (EC50) confidence intervals overlapped, indicating no difference between the two methods; the 4-PL model was chosen because of its fewer parameters. The Limits of Detection (LOD) calculated using the 4-PL equation was 0.818 ng/mL, with a 95% confidence interval of 0.526-1.143 ng/mL. This value falls within the estimated range of 0.5 to 10 ng/mL found in the first investigation. Not only was the linear component of the data curve successfully represented by this study's use of the 4-PL model, but the model was also successful in representing the entire date curve.

Comparison of Kinetic Models Applied for Transport Description in Polymer Inclusion Membranes.

Five mathematical models for transport description in polymer inclusion membranes (PIMs) were presented and compared via regression analysis. The applicability of the models was estimated through the examination of experimental data of Zn(II), Cd(II), Pb(II), and Cu(II) ions transported by typical carriers. In four kinetic models, a change in the feed and stripping solution volume was taken into account. The goodness of fit was compared using the standard error of the regression, Akaike information criterion (AIC), Bayesian (Schwarz) information criterion (BIC), and Hannan-Quinn information criterion (HQC). The randomness distribution in the data was confirmed via a nonparametric runs test. Based on these quantities, appropriate models were selected.

Kinetic Analysis of the Adsorption of Ethyl Violet onto Graphene Oxide Sheets Integrated with Gold Nanoparticles

An example of biosorption is when the sorbent is made from a biodegradable material. Biosorption is now being seen as a simple, cost-effective, and environmentally acceptable alternative to traditional pollution treatment methods. Bioremediation is one of the branches of bioremediation that is used to minimise pollution in the context of incorrect dye waste disposal. The sorption isotherm of Ethyl Violet onto graphene oxide were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) that showed that the pseudo-second-order model was the best which was the same finding from the original published work. The calculated evidence ratio was 11 with an AICc probability value of 0.91 indicating that the best model was at least 11 times better than the nearest best model, which was pseudo-1st. Further analysis is needed to provide proof for the mechanism usually tied to this kinetic. Nonlinear regression analysis using the pseudo-2nd order model for the highest concentration tested, which was 10 mM, gave values of equilibrium sorption capacity qe of 30.928 mg/g (95% confidence interval from 29.328 to 32.527) and a value of the pseudo-2nd-order rate constant, k2 of 0.020 (95% confidence interval from 0.011 to 0.028).

Kinetic Analysis of the Adsorption of Cibacron Blue onto Bean Peel

Biosorption is a kind of sorption technology in which the sorbent is derived from a biological source. At the moment, biosorption is seen as a simple, cost-effective, and environmentally friendly process that might be employed as a viable alternative to conventional techniques of pollution removal. When it comes to improper textile waste disposal, it falls under one of the branches of bioremediation that is used to reduce contamination in the setting of improper textile waste disposal. The sorption isotherm of Cibacron Blue onto bean peel were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. The Elovich model was the poorest in fitting the curve based on visual observation and the best was pseudo-2nd order based on statistical analysis such as root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC). Nonlinear regression analysis using the pseudo-2nd order model gave values of equilibrium sorption capacity qe of 6.164 mg/g (95% confidence interval from 5.918 to 6.410 ) and a value of the pseudo-2nd-order rate constant, k2 of 0.034 (95% confidence interval from 0.024 to 0.045). Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

Kinetics Modeling on the Biosorption of Remazol Black B Dye by Aspergillus flavus

Azo dyes, such as Remazol Black B, are different from conventional dyes in that they establish covalent bonds with textile fibers like cotton. They are widely utilized in the textile industry because of their favorable properties of bright color, water resistance, simple application procedures, and low energy consumption. Their discharge into receiving streams has major environmental consequences, such as reducing photosynthesis in aquatic life due to lower light penetration. The biosorption isotherm data of Remazol Black B dye biosorption by Aspergillus flavus were investigated using two models—pseudo-1st order and pseudo-2nd order—and fitted using non-linear regression. The pseudo-1st order model was found to be the best by statistical analysis using root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC), and Hannan–Quinn information criterion (HQC). At 250 mg/L, kinetic analysis using the pseudo-1st order model yielded an equilibrium sorption capacity qe of 4.61 mg/g (95 % confidence interval from 4.54 to 4.68) and a pseudo-1st-order rate constant, k1 of 0.15 (95% C.I. from 0.128 to 0.164).

Kinetic Analysis of the Adsorption of Malachite Green onto Graphene Oxide Sheets Integrated with Gold Nanoparticles

Malachite green is extensively used in the textile dye industry and in agriculture as fish pests’ pesticide. Biosorption is a type of sorption technique that uses a biological sorbent. As of now, biosorption is viewed as a simple and cost-effective process that might be used as an alternative to traditional pollution treatment methods. Bioremediation is one of the branches of bioremediation that is used to minimise pollution in the context of incorrect textile waste disposal. The sorption isotherm of Malachite Green onto graphene oxide were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. The Elovich model was the poorest in fitting the curve based on visual observation and the best was pseudo-2nd order based on statistical analysis such as root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC). Nonlinear regression analysis using the pseudo-2nd order model gave values of equilibrium sorption capacity qe of 6.164 mg/g (95% confidence interval from 5.918 to 6.410) and a value of the pseudo-2nd-order rate constant, k2 of 0.034 (95% confidence interval from 0.024 to 0.045). Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

Kinetic Analysis of the Adsorption of Chromium onto Calcium Alginate Nanoparticles

The widespread use of chromium in industrial applications such as leather tanning, metallurgy, electroplating, and refractory materials has resulted in it being one of the most harmful trace elements to be introduced into surface and ground waters. The sorption isotherm of chromium sorption onto calcium alginate nanoparticles were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. The Elovich model was the poorest in fitting the curve based on visual observation followed by the pseudo-1st order. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) that showed that the pseudo-1ST order model is the best model. Kinetic analysis using the pseudo-1st order model at 400 mg/L 4-BDE gave a value of equilibrium sorption capacity qe of 31.89 mg g-1 (95% confidence interval from 30.37 to 33.42) and a value of the pseudo-1st-order rate constant, k1 of 0.22 (95% confidence interval from 0.019 to 0.025). Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

Evaluating information criteria for selecting spatial processes

Information criteria have been widely used in many quantitative applications as an effort to select the most appropriate model that describes well enough the unknown population behavior for a given dataset. Studies have shown that their performance depends on several elements and the selection of the best fitted model is not always the same for all criteria. For this purpose, this research evaluates the performance of the three most often used information criteria, such as the Akaike information criterion, the Bayesian information criterion and Hannan and Quinn information criterion, for selecting spatial processes, taking into account that the sample in spatial analysis is regarded as a realization of a spatial process that incorporates the spatial dependence between the observations. Using a Monte Carlo analysis for the three most frequently applied in practice spatial processes, such as the first-order spatial autoregressive process, SAR(1), the first-order spatial moving average process, SMA(1), and the mixed spatial autoregressive moving average process, SARMA(1, 1), this study finds that these information criteria can assist the analyst to select the true process, but their behavior depends on sample size as well as on the magnitude of the spatial parameters, leading occasionally to alternative competitive processes.

Kinetic Studies on the Biosorption of the Brominated Flame Retardant 4-Dibromodiphenyl ether (BDE-3) using Coconut Palm Leaf Powders

Methods such as membrane isolation, ion replacements, precipitation, transformation and biosorption are proven approaches to contaminant control. Biosorption has all of these technological features including low operating costs, very efficient detoxifying of toxicities at low volumes, minimal amounts of removal components and nutrient requirement, as well as bacterial remediation, which are limited to the presence of heavy metals and other toxicants. The biosorption of BDE-3 on coconut leaves powder on the biosorption of BDE-3 from coconut leaves powder were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) showed that the Pseudo-2nd order model is the best model. Kinetic analysis using the Pseudo-2nd order model gave a value of equilibrium sorption capacity qe for 0.01 g per L adsorbent of 488.16 mg g-1 (95% confidence interval from 463.68 to 512.64) and a value of the Pseudo-2nd-order rate constant, k2 of 0.00019 (95% confidence interval from 0.00010 to 0.00027) while the equilibrium sorption capacity qe for 0.002 g per L adsorbent of 2403.61 mg g-1 (95% confidence interval from 2313.99 to 2493.22) and a value of the Pseudo-2nd-order rate constant, k2 of 0.000043 (95% confidence interval from 0.000027 to 0.000059). These calculated values will be very useful in designing effective sorption experiment and understanding the limitations of the system developed.

Model Selection Procedures in Bounds Test of Cointegration: Theoretical Comparison and Empirical Evidence

Only unstructured single-path model selection techniques, i.e., Information Criteria, are used by Bounds test of cointegration for model selection. The aim of this paper was twofold; one was to evaluate the performance of these five routinely used information criteria {Akaike Information Criterion (AIC), Akaike Information Criterion Corrected (AICC), Schwarz/Bayesian Information Criterion (SIC/BIC), Schwarz/Bayesian Information Criterion Corrected (SICC/BICC), and Hannan and Quinn Information Criterion (HQC)} and three structured approaches (Forward Selection, Backward Elimination, and Stepwise) by assessing their size and power properties at different sample sizes based on Monte Carlo simulations, and second was the assessment of the same based on real economic data. The second aim was achieved by the evaluation of the long-run relationship between three pairs of macroeconomic variables, i.e., Energy Consumption and GDP, Oil Price and GDP, and Broad Money and GDP for BRICS (Brazil, Russia, India, China and South Africa) countries using Bounds cointegration test. It was found that information criteria and structured procedures have the same powers for a sample size of 50 or greater. However, BICC and Stepwise are better at small sample sizes. In the light of simulation and real data results, a modified Bounds test with Stepwise model selection procedure may be used as it is strongly theoretically supported and avoids noise in the model selection process.

Kinetics of the Removal of Polybrominated Diphenyl Ethers from Aqueous Solutions by Using pressure steam–washed Black Tea

Established approaches for the management of contaminants include things like membrane separation, ion exchange, precipitation, transformation and biosorption. Of all of these technologies, biosorption has lots of features that include low running expenditures, very effective detoxification of toxicants at low levels, low quantity of removal components as well as does not require nutrient needs as with bacterial-based remediation, theaforementioned being restricted to the existence of heavy metals and other toxicants. The biosorption of BDE-3 on spent black tea was successfully fitted to three models—pseudo-1st, pseudo-2nd and Elovich. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), accuracy factor (AF), bias factor (BF), corrected AICc Bayesian Information Criterion (BIC), (Akaike Information Criterion) and Hannan–Quinn information criterion (HQC) showed that the pseudo-second order model is the best model giving valuable parameters such as the equilibrium sorption capacity qe and the pseudo-second-order rate constant, k2, which can be further utilized in isothermal modelling analysis. Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

FARIMA MODELING OF SUNSPOT HALE CYCLES TIME SERIES

The influence of solar activity on climate system at regional or global scales cannot be neglected. In this study, we will stimulate full-length sunspot time series (1932–2014) and all four Hale cycles by fractional auto regressive integrated moving average (FARIMA ([Formula: see text], [Formula: see text], [Formula: see text])) model. By minimizing Akaike information criterion (AIC), Bayesian–Schwarz information criterion (BIC) and Hannan–Quinn information criterion (HIC), the best FARIMA model for full-length sunspot time series is [Formula: see text] where [Formula: see text] is the back shift operator and [Formula: see text] is a white noise.

Kinetic Analysis of the Adsorption of the Brominated Flame Retardant 4-bromodiphenyl Ether onto Biochar-immobilized Sphingomonas sp.

4-bromophenyl phenyl ether or 4-bromodiphenyl ether (4-BDE) is a less brominated PBDE, which are brominated flame retardants (BFRs), that has come into importance when it was detected as the main pollutant in Sungai Buah, a tributary to the Sungai Semenyih that have recently caused the pollution of drinking waters in the Semenyih Water Treatment Plant, Putrajaya Selangor that led to water shortage for many days to affecting many areas. 4-BDE is also a recalcitrant priority pollutant where it is barely degraded at all. Many of the PBDE can cause developmental neurotoxicity. The absorption kinetics data of biosorption isotherm on the biosorption of 4-BDE onto Biochar-immobilized Sphingomonas sp. were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. The Elovich model was the poorest in fitting the curve based on visual observation followed by the pseudo-1st order. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) that showed that the pseudo-1ST order model is the best model. Kinetic analysis using the pseudo-1st order model at 400 mg/L 4-BDE gave a value of equilibrium sorption capacity qe of 31.89 mg g-1 (95% confidence interval from 30.37 to 33.42) and a value of the pseudo-1st-order rate constant, k1 of 0.22 (95% confidence interval from 0.019 to 0.025). Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

Kinetic Analysis of the Adsorption of Glyphosate onto Palm Oil Fronds Activated Carbon

Existing techniques for the treatment of pollutants include membrane separation, ion exchange, precipitation, transformation and biosorption. Of all of this technology, biosorption has several positive aspects which include low operating expenses, very efficient detoxification of toxicants at low concentrations, low amount of disposal materials and does not need nutrient requirements as in bacterial-based remediation, the latter of which is limited by the presence of heavy metals and other toxicants. The biosorption of glyphosate on palm oil fronds activated carbon can be an efficient and low-cost tool for remediation of glyphosate. The absorption kinetics data of biosorption isotherm on the biosorption of glyphosate on palm oil fronds activated carbon were analyzed using three models—pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. The Elovich model was the poorest in fitting the curve based on visual observation followed by the pseudo-1st order. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannan–Quinn information criterion (HQC) that showed that the pseudo-second order model is the best model. Kinetic analysis using the pseudo-second order model at 250 mg/L glyphosate gave a value of equilibrium sorption capacity qe of 94.12 mg g-1 (95% confidence interval from 89.913 to 98.332) and a value of the pseudo-second-order rate constant, k2 of 0.02 (95% confidence interval from 0.012 to 0.023). Further analysis is needed to provide proof for the chemisorption mechanism usually tied to this kinetic.

Modified Beta Linear Exponential Distribution with Hydrologic Applications

In this paper, we introduce a flexible modified beta linear exponential (MBLE) distribution. Our motivation, besides others are there, dues to its ability in hydrology applications. We investigate a set of its statistical properties for supporting such applications, like moments, moment generating function, conditional moments, mean deviations, entropy, mean and variance (reversed) residual life and maximum likelihood estimators with observed information matrix. The distribution can accommodate both decreasing and increasing hazard rates as well as upside down bathtub and bathtub shaped hazard rates. Moreover, several distributions arise as special cases of the distribution. The MBLE distribution with others are fitted to two hydrology data sets. It is shown that, the MBLE distribution is the best fit among the compared distributions based on nine goodness-of-fit statistics among them the Corrected Akaike information criterion, Hannan–Quinn information criterion, Anderson–Darling and Kolmogorov–Smirnov p value. Consequently, some parameters of these data are obtained such as return level, conditional mean, mean deviation about the return level, risk of failure for designing hydraulic structures. Finally, we hope that this model will be able to attract wider applicability in hydrology and other life areas.

Estimation of the Residuals and the Coefficients Test of the Full Information Maximum Likelihood of System Equations of 4 Spot Exchange Rates in Terms of CAD/USD, DKK/USD, CHF/USD and JPY/USD.

In this article, we have tested the full information maximum likelihood, (FIML) of the natural logarithmic monthly returns of the CAD/USD, DKK/USD, CHF/USD and JPY/USD spot exchange rates. We have applied a system of four equations of the spot exchange rates to test and spot volatility clusters.The best fit model that helps the arbitrageurs to craft their investment strategy in terms of buying or holding large portfolios of spot exchange rates is the CAD/USD represented by equation 1. It has the largest value of the log likelihood and average log likelihood value. The values are 507.9283 and 2.49 respectively. In addition, the CAD/USD spot exchange rate has the lowest error term value of the Akaike, Schwarz and Hannan - Quinn information criterion. The numerical values are -4.97, -4.95 and -4.96 respectively. Moreover, the CAD/USD spot exchange rate has the lowest standard error, which equals to 0.001450. The data that we have used started from 01/10/2000 to 01/09/2017 and represent the CAD/USD, DKK/USD, CHF/USD and JPY/USD spot exchange rates, which total to 204 observations. The data was obtained from the Federal Reserve statistical release department and it is denoted by the symbol, H.10.