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Journal articles on the topic 'Jackknife Technique'

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Published: 3 June 2025
Last updated: 20 July 2025

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1

Matyska, L., and J. Kovář. "Comparison of several non-linear-regression methods for fitting the Michaelis-Menten equation." Biochemical Journal 231, no. 1 (1985): 171–77. http://dx.doi.org/10.1042/bj2310171.

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The known jackknife methods (i.e. standard jackknife, weighted jackknife, linear jackknife and weighted linear jackknife) for the determination of the parameters (as well as of their confidence regions) were tested and compared with the simple Marquardt's technique (comprising the calculation of confidence intervals from the variance-co-variance matrix). The simulated data corresponding to the Michaelis-Menten equation with defined structure and magnitude of error of the dependent variable were used for fitting. There were no essential differences between the results of both point and interval
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2

Broemeling, L. D., and R. R. Wolfe. "Measuring intrasubject variability: use of the jacknife in doubly labeled water experiments." Journal of Applied Physiology 75, no. 4 (1993): 1507–12. http://dx.doi.org/10.1152/jappl.1993.75.4.1507.

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The doubly labeled water technique measures energy expenditure; however, very little has appeared in the literature regarding estimation of the intrasubject variation. By use of a statistical resampling procedure called the jackknife, the standard deviation of the determination of energy expenditure in each subject is evaluated. Jackknife methods exploit the regression techniques that are already used with the doubly labeled water technique and are very easy to implement. Estimates of sample sizes for future experiments can easily be done with the jackknife. These formulas give the number of d
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3

Zitzmann, Steffen, Sebastian Weirich, and Martin Hecht. "Accurate Standard Errors in Multilevel Modeling with Heteroscedasticity: A Computationally More Efficient Jackknife Technique." Psych 5, no. 3 (2023): 757–69. http://dx.doi.org/10.3390/psych5030049.

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In random-effects models, hierarchical linear models, or multilevel models, it is typically assumed that the variances within higher-level units are homoscedastic, meaning that they are equal across these units. However, this assumption is often violated in research. Depending on the degree of violation, this can lead to biased standard errors of higher-level parameters and thus to incorrect inferences. In this article, we describe a resampling technique for obtaining standard errors—Zitzmann’s jackknife. We conducted a Monte Carlo simulation study to compare the technique with the commonly us
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Rothpearl, Allen. "The Jackknife Technique in Statistical Analysis." Chest 95, no. 4 (1989): 940. http://dx.doi.org/10.1378/chest.95.4.940b.

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Mousavi, S. M., R. Tavakkoli-Moghaddam, A. Azaron, S. M. H. Mojtahedi, and H. Hashemi. "Risk assessment for highway projects using jackknife technique." Expert Systems with Applications 38, no. 5 (2011): 5514–24. http://dx.doi.org/10.1016/j.eswa.2010.10.085.

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Kaufman, Daniel. "Measuring Archaeological Diversity: An Application of the Jackknife Technique." American Antiquity 63, no. 1 (1998): 73–85. http://dx.doi.org/10.2307/2694777.

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The jackknife technique is applied here to measures of diversity in an archaeological context. As described, the technique requires no assumptions about the underlying structure of the data being analyzed and, thus, is offered as an alternative to simulation and regression approaches. Most important, with jackknifing it is possible to attach statistical significance to differences in diversity, allowing for more meaningful comparisons between archaeological assemblages.
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Priyanka, Kumari. "Tuning design weights to deal with non-response in successive sampling." Model Assisted Statistics and Applications 16, no. 2 (2021): 97–108. http://dx.doi.org/10.3233/mas-210522.

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The estimation of finite population mean at current occasion in two occasion successive sampling in presence of non-response is investigated using tuned jackknife estimators. Based on the availability of auxiliary information at population level (Info U) and sample level (Info s) and using tuned jackknife technique, estimators have been proposed. Estimator of variance of proposed estimators have also been discussed. Different cases of occurance of non-response have been explored. The estimators are mutually compared. The properties of these estimators are studied via simulation study using nat
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Sohil, Fariha, Muhammad Umair Sohail, Javid Shabbir, and Sat Gupta. "Jackknife winsorized variance estimator under imputed data." Statistics in Transition New Series 23, no. 2 (2022): 17–32. http://dx.doi.org/10.2478/stattrans-2022-0014.

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Abstract In the present study, we consider the problem of missing and extreme values for the estimation of population variance. The presence of extreme values either in the study variable, or the auxiliary variable, or in both of them, can adversely affect the performance of the estimation procedure. We consider three different situations for the presence of extreme values and also consider jackknife variance estimators for the population variance by handling these extreme values under stratified random sampling. Bootstrap technique ABB is carried out to understand the relative relationship mo
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Srinivas, V. Satya, A. D. Sarma, and Hema K. Achanta. "Modeling of Ionospheric Time Delay Using Anisotropic IDW With Jackknife Technique." IEEE Transactions on Geoscience and Remote Sensing 54, no. 1 (2016): 513–19. http://dx.doi.org/10.1109/tgrs.2015.2461017.

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Koç, Tuba, and Haydar Koç. "A New Effective Jackknifing Estimator in the Negative Binomial Regression Model." Symmetry 15, no. 12 (2023): 2107. http://dx.doi.org/10.3390/sym15122107.

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The negative binomial regression model is a widely adopted approach when dealing with dependent variables that consist of non-negative integers or counts. This model serves as an alternative regression technique for addressing issues related to overdispersion in count data. Typically, the maximum likelihood estimator is employed to estimate the parameters of the negative binomial regression model. However, the maximum likelihood estimator can be highly sensitive to multicollinearity, leading to unreliable results. To eliminate the adverse effects of multicollinearity in the negative binomial r
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Miroshnychenko, V. O. "Fast calculations of Jackknife covariance matrix estimator." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 1 (2021): 27–36. http://dx.doi.org/10.17721/1812-5409.2021/1.3.

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We consider data in which each observed subject belongs to one of different subpopulations (components). The true number of component which a subject belongs to is unknown, but the researcher knows the probabilities that a subject belongs to a given component (concentration of the component in the mixture). The concentrations are different for different observations. So the distribution of the observed data is a mixture of components’ distributions with varying concentrations. A set of variables is observed for each subject. Dependence between these variables is described by a nonlinear regres
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Epishkin, D. V. "Improving magnetotelluric data processing methods." Moscow University Bulletin. Series 4. Geology, no. 4 (August 28, 2016): 40–46. http://dx.doi.org/10.33623/0579-9406-2016-4-40-46.

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A magnetotelluric data processing code has been developed, which demonstrates high robustness to intense electromagnetic noise occurring in measured MT data. Key features of the code are specific approach for estimating different transfer functions and capability to utilize all four channels acquired at remote reference station. The code utilizes various techniques to reduce estimate errors, including robust Huber estimator, jackknife approach, improved remote reference technique and compensating for overestimation of power spectra. The proposed code has shown high efficiency in processing of
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Ehsan, Asma, Muhammad K. Mahmood, Yaser D. Khan, Omar M. Barukab, Sher A. Khan, and Kuo-Chen Chou. "iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5- Step Rule and General Pseudo Amino Acid Composition." Current Genomics 20, no. 2 (2019): 124–33. http://dx.doi.org/10.2174/1389202920666190325162307.

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Background:In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests.Methods:With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effec
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Rodríguez Castro, Jorge Homero. "Evaluación del crecimiento de la jaiba Callinectes sapidus en la costa de Tamaulipas, México: comparación de tres métodos indirectos." Revista de Biología Tropical 64, no. 2 (2016): 821. http://dx.doi.org/10.15517/rbt.v64i2.16958.

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<strong>Abstract: Evaluation of the growth of the blue crab <em>Callinectes sapidus</em> in coastal Tamaulipas, Mexico: comparison of three indirect methods.</strong> The blue crab (<em>Callinectes sapidus</em>) is one of the major fisheries of the state of Tamaulipas, Mexico; both in volume and selling price, such as employment generation, but has little information on its biological characteristics. The aim of this study was to evaluate the growth parameters of the blue crab, establishing the most appropriate method to do it. Length frequency of 17 814 cra
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Maia, Aline de H. N., Alfredo J. B. Luiz, and Clayton Campanhola. "Statistical Inference on Associated Fertility Life Table Parameters Using Jackknife Technique: Computational Aspects." Journal of Economic Entomology 93, no. 2 (2000): 511–18. http://dx.doi.org/10.1603/0022-0493-93.2.511.

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Cheung, Yin-Wong, and Wenhao Wang. "A Jackknife Model Averaging Analysis of RMB Misalignment Estimates." Journal of International Commerce, Economics and Policy 11, no. 02 (2020): 2050007. http://dx.doi.org/10.1142/s1793993320500076.

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We adopt the Jackknife Model Averaging (JMA) technique to conduct a meta-regression analysis of 925 renminbi (RMB) misalignment estimates generated by 69 studies. The JMA method accounts for model selection and sampling uncertainties, and allows for non-nested model specifications and heteroskedasticity in assessing effects of study characteristics. The RMB misalignment estimates are found to be systematically affected by the choices of data, the theoretical setup and the empirical strategy, in addition to publication attributes of these studies. These study characteristic effects are quite ro
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Tang, Hua, Yunchun Yang, Chunmei Zhang, et al. "Predicting Presynaptic and Postsynaptic Neurotoxins by Developing Feature Selection Technique." BioMed Research International 2017 (2017): 1–4. http://dx.doi.org/10.1155/2017/3267325.

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Presynaptic and postsynaptic neurotoxins are proteins which act at the presynaptic and postsynaptic membrane. Correctly predicting presynaptic and postsynaptic neurotoxins will provide important clues for drug-target discovery and drug design. In this study, we developed a theoretical method to discriminate presynaptic neurotoxins from postsynaptic neurotoxins. A strict and objective benchmark dataset was constructed to train and test our proposed model. The dipeptide composition was used to formulate neurotoxin samples. The analysis of variance (ANOVA) was proposed to find out the optimal fea
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Lukic, Dejan, Zoran Radovanovic, Tomislav Petrovic, Milan Breberina, Andrija Golubovic, and Svetlana Skoric-Jokic. "Oncologic superiority of extralevator abdominoperineal excision for low rectal cancer." Archive of Oncology 21, no. 1 (2013): 11–13. http://dx.doi.org/10.2298/aoo1301011l.

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Background: Rectal cancer treatment has been dramatically improved during the last two decades in terms of a lower local recurrence rate and prolonged survival. This improvement was achieved mainly due to a better surgical technique (implementation of a total mesorectal excision-TME) and neoadjuvant chemo and radio therapy. A more radical approach to abdominoperineal excision, extralevator abdominoperineal excision technique in the prone Jackknife position, may improve the oncological outcome. The aim of this study is to show our early experience by using extralevator abdominoperineal excision
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Srisodaphol, Wuttichai, and Noppakun Tongmol. "Improved Estimators of the Mean of a Normal Distribution with a Known Coefficient of Variation." Journal of Probability and Statistics 2012 (2012): 1–5. http://dx.doi.org/10.1155/2012/807045.

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This paper is to find the estimators of the meanθfor a normal distribution with meanθand varianceaθ2,a>0,θ>0. These estimators are proposed when the coefficient of variation is known. A mean square error (MSE) is a criterion to evaluate the estimators. The results show that the proposed estimators have preference for asymptotic comparisons. Moreover, the estimator based on jackknife technique has preference over others proposed estimators with some simulations studies.
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Huang, Y. B., and H. Chi. "Life tables of Bactrocera cucurbitae (Diptera: Tephritidae): with an invalidation of the jackknife technique." Journal of Applied Entomology 137, no. 5 (2012): 327–39. http://dx.doi.org/10.1111/jen.12002.

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21

Novia Nur Rohma. "Estimation of Ordinary Kriging Method with Jackknife Technique on Rainfall Data in Malang Raya." International Journal on Information and Communication Technology (IJoICT) 8, no. 2 (2022): 22–39. http://dx.doi.org/10.21108/ijoict.v8i2.678.

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Geostatistics is a science that focuses on spatial data. In geostatistics, there is an estimation method to handle variables whose values ​​vary with the change in location or place, which are called regionalized variables. The estimation method used to handle regionalized variables is called the kriging method. In the ordinary kriging method it is necessary to take into account the semivariogram. Rain is a process of falling water from the clouds to the earth. Rain is measured through rainfall. The purpose of this study was to determine estimation of the ordinary kriging method on normall
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Lee, Soojeong. "Improved Confidence Interval Estimation for Oscillometric Blood Pressure Measurement by Combining Bootstrap-After-Jackknife Function with Non-Gaussian Models." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/231925.

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Confidence intervals (CIs) are generally not provided along with estimated systolic blood pressure (SBP) and diastolic blood pressure (DBP) measured using oscillometric blood pressure devices. No criteria exist to determine the CI from a small sample set of oscillometric blood pressure measurements. We provide an extended methodology to improve estimation of CIs of SBP and DBP based on a nonparametric bootstrap-after-jackknife function and a Bayesian approach. We use the nonparametric bootstrap-after-jackknife function to reduce maximum amplitude outliers. Improved pseudomaximum amplitudes (PM
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23

Ashe, Frank. "An Essay at Measuring the Variance of Estimates of Outstanding Claim Payments." ASTIN Bulletin 16, S1 (1986): S99—S113. http://dx.doi.org/10.1017/s0515036100011685.

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AbstractThe variance of statistical estimates of outstanding claim payments for long-tailed general insurance portfolios is examined. The variance's three components are discussed. As there is no accepted technique for measuring this variance three methods are investigated empirically for its measurement—a parametric method, the jackknife method, and the bootstrap method. No method stands out as superior to the others and it is recommended that all three be evaluated and used to gauge the possible errors in the estimation of outstanding claims.
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Wichitchan, Supawadee, Athipakon Nathomthong, Pannarat Guayjarernpanishk, and Nipaporn Chutiman. "Enhanced Ratio-Type Estimators in Adaptive Cluster Sampling Using Jackknife Method." Mathematics 13, no. 12 (2025): 2020. https://doi.org/10.3390/math13122020.

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Adaptive cluster sampling is a methodology designed for data collection in contexts where the population is rare and spatially clustered. This approach has been effectively applied in various disciplines, including epidemiology and resource management. The present study introduces novel estimators that incorporate auxiliary variable information to improve estimation efficiency. These estimators were developed using the jackknife resampling technique to improve the performance of ratio-type estimators. Theoretical properties, including bias and mean square error (MSE), were derived, and a simul
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Mahmood, Muhammad Khalid, Asma Ehsan, Yaser Daanial Khan, and Kuo-Chen Chou. "iHyd-LysSite (EPSV): Identifying Hydroxylysine Sites in Protein Using Statistical Formulation by Extracting Enhanced Position and Sequence Variant Feature Technique." Current Genomics 21, no. 7 (2020): 536–45. http://dx.doi.org/10.2174/1389202921999200831142629.

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Introduction: Hydroxylation is one of the most important post-translational modifications (PTM) in cellular functions and is linked to various diseases. The addition of one of the hydroxyl groups (OH) to the lysine sites produces hydroxylysine when undergoes chemical modification. Methods: The method which is used in this study for identifying hydroxylysine sites based on powerful mathematical and statistical methodology incorporating the sequence-order effect and composition of each object within protein sequences. This predictor is called "iHyd-LysSite (EPSV)" (identifying hydroxylysine site
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Andini, Agita, Etis Sunandi, Pepi Novianti, Idhia Sriliana, and Winalia Agwil. "Perbandingan Metode Regresi Ridge dan Jackknife Ridge Regression pada Data Tingkat Pengangguran Terbuka." Limits: Journal of Mathematics and Its Applications 22, no. 1 (2025): 77–84. https://doi.org/10.12962/limits.v22i1.3374.

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Regression analysis is a statistical technique used to analyze the relationship between predictor and response variables. One of the parameter estimation methods commonly used for regression analysis is Ordinary Least Squares. This method produces unbiased and efficient estimates, known as BLUE (Best Linear Unbiased Estimator). In multiple linear regression analysis involving more than one predictor variable, it is essential to meet model assumptions such as the absence of multicollinearity. Multicollinearity is a condition where predictor variables have a high correlation, which can disrupt t
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Wee Soh, Kian, Thomas Lumley, Cameron Walker, and Michael O’Sullivan. "Model averaging with the hybrid model: An asymptotic study and demonstration." Statistical Methods in Medical Research 31, no. 4 (2022): 658–72. http://dx.doi.org/10.1177/09622802211041750.

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In this paper, we present a new model averaging technique that can be applied in medical research. The dataset is first partitioned by the values of its categorical explanatory variables. Then for each partition, a model average is determined by minimising some form of squared errors, which could be the leave-one-out cross-validation errors. From our asymptotic optimality study and the results of simulations, we demonstrate under several high-level assumptions and modelling conditions that this model averaging procedure may outperform jackknife model averaging, which is a well-established tech
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Shafique, Hassan, Asghar Ali Shah, Muhammad Aasim Qureshi, Muhammad Khurram Ehsan, and Muhammad Rizwan Amirzada. "Machine Learning Empowered Efficient Intrusion Detection Framework." VFAST Transactions on Software Engineering 10, no. 2 (2022): 27–35. http://dx.doi.org/10.21015/vtse.v10i2.1017.

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In modern era security is becoming major and basic need of any system. Protecting of a system from unauthorized access is very important for a network system. Network security is turning out to be an influential subject in information technology territory. Hackers and squatters commit uncountable successful attempts to intrude into networks. Intrusion Detection System plays a vital role in a network security to identify and detect the anomalies in a security system of network. The performance of IDS can be measured through its intelligence, efficiency and accurate detection of unknown and know
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Marange, Chioneso Show, and Yongsong Qin. "An Empirical Likelihood Ratio-Based Omnibus Test for Normality with an Adjustment for Symmetric Alternatives." Journal of Probability and Statistics 2021 (March 2, 2021): 1–18. http://dx.doi.org/10.1155/2021/6661985.

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An omnibus test for normality with an adjustment for symmetric alternatives is developed using the empirical likelihood ratio technique. We first transform the raw data via a jackknife transformation technique by deleting one observation at a time. The probability integral transformation was then applied on the transformed data, and under the null hypothesis, the transformed data have a limiting uniform distribution, reducing testing for normality to testing for uniformity. Employing the empirical likelihood technique, we show that the test statistic has a chi-square limiting distribution. We
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Caissie, Daniel, Nassir El-Jabi, and Cindie Hébert. "Comparison of hydrologically based instream flow methods using a resampling technique." Canadian Journal of Civil Engineering 34, no. 1 (2007): 66–74. http://dx.doi.org/10.1139/l06-095.

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The protection of fish habitat against the impact of water extraction in rivers is a recurring problem in water resources management. As such, a wide range of methodologies is available for the calculation of instream flows. This study focuses on historical streamflow methods that rely solely on hydrometric data for instream flow evaluation. The objectives of the study are to compare different historical streamflow methods and use a jackknife resampling technique to assess the variability of instream flow estimates. Results showed that methods based on a percentage of mean annual flow (MAF) ge
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Carbonara, Pierluigi, Teresa Silecchia, Maria Spedicato, Alessandra Acrivulis, and Giuseppe Lembo. "A GEOSTATISTICAL APPROACH TO THE ASSESSMENT OF THE SPATIAL DISTRIBUTION OF PARAPENAEUS LONGIROSTRIS (LUCAS, 1846) IN THE CENTRAL-SOUTHERN TYRRHENIAN SEA." Crustaceana 72, no. 9 (1999): 1093–108. http://dx.doi.org/10.1163/156854099504040.

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AbstractThe spatial distribution of the abundance indices of the deep-water rose shrimp Parapenaeus longirostris was investigated applying geostatistical techniques on data collected in the central southern Tyrrhenian Sea from bottom trawl surveys carried out in the autumn since 1994. Experimental variograms (auto and cross) were constructed on the variable "abundance index", expressed in kg/km2, and those variogram models best describing the spatial continuity were detected and validated by the jackknife technique. The spatial structure of the "abundance index", exhibiting a similar pattern t
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G. Gogorza, C. S., S. Torcida, A. M. Sinito, and M. A. E. Chaparro. "Application of the pseudo-Thellier technique to a paleomagnetic record from lake El Trébol (Patagonia, Argentina)." Geofísica Internacional 47, no. 4 (2008): 319–27. http://dx.doi.org/10.22201/igeof.00167169p.2008.47.4.2144.

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 The pseudo-Thellier technique was applied to obtain relative paleointensity determinations using a sediment core from Lake El Tre?bol (Patagonia, Argentina).
 
 
 
 
 Measurements of intensity of natural remanent magnetization left (NRMleft) after AF demagnetization versus intensity of anhysteric remanent magnetization gained (ARMgained) at the same peak were carried out on a set of samples. Two versions of a jackknife resampling scheme were used to get error estimates on the paleointensity.
 
 
 
 
 The pseudo-Thellier pal
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رضا, صباح منفي, and علاء حسين صبري. "Improving " Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application." Journal of Economics and Administrative Sciences 25, no. 113 (2019): 462–74. http://dx.doi.org/10.33095/jeas.v25i113.1707.

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Abstract
 Most of the robust methods based on the idea of ​​sacrificing one side versus promotion of another, the artificial intelligence mechanisms try to balance weakness and strength to make the best solutions in a random search technique. In this paper, a new idea is introduced to improve the estimators of parameters of linear simultaneous equation models that resulting from the Jackknife Instrumental Variable Estimation method (JIVE) by using a class of immune algorithm which called Clonal Selection Algorithm (CSA) and better estimates are obtained using one of the robust criterion w
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Monchot, Hervé, and Jacques Léchelle. "Statistical nonparametric methods for the study of fossil populations." Paleobiology 28, no. 1 (2002): 55–69. http://dx.doi.org/10.1666/0094-8373(2002)028<0055:snmfts>2.0.co;2.

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The precise knowledge of the number and nature of the species belonging to a fossil assemblage as well as of the structure of each species (e.g., age, sex) is of great importance in paleontology. Mixture analysis based on the method of maximum likelihood is a modern statistical technique that concerns the problem of samples consisting of several components, the composition of which is not known. Nonparametric bootstrap and jackknife techniques are used to calculate a confidence interval for each estimated parameter (prior probability, mean, standard deviation) of each group. The bootstrap meth
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Feng, Peng-Mian, Hao Lin, and Wei Chen. "Identification of Antioxidants from Sequence Information Using Naïve Bayes." Computational and Mathematical Methods in Medicine 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/567529.

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Antioxidant proteins are substances that protect cells from the damage caused by free radicals. Accurate identification of new antioxidant proteins is important in understanding their roles in delaying aging. Therefore, it is highly desirable to develop computational methods to identify antioxidant proteins. In this study, a Naïve Bayes-based method was proposed to predict antioxidant proteins using amino acid compositions and dipeptide compositions. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife tes
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Feng, Peng-Mian, Hui Ding, Wei Chen, and Hao Lin. "Naïve Bayes Classifier with Feature Selection to Identify Phage Virion Proteins." Computational and Mathematical Methods in Medicine 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/530696.

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Knowledge about the protein composition of phage virions is a key step to understand the functions of phage virion proteins. However, the experimental method to identify virion proteins is time consuming and expensive. Thus, it is highly desirable to develop novel computational methods for phage virion protein identification. In this study, a Naïve Bayes based method was proposed to predict phage virion proteins using amino acid composition and dipeptide composition. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In
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Confalonieri, Roberto, Daniela Stroppiana, Mirco Boschetti, Davide Gusberti, Stefano Bocchi, and Marco Acutis. "Analysis of rice sample size variability due to development stage, nitrogen fertilization, sowing technique and variety using the visual jackknife." Field Crops Research 97, no. 2-3 (2006): 135–41. http://dx.doi.org/10.1016/j.fcr.2005.09.008.

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Johnson, LeeAnn K., Mary B. Brown, Ethan A. Carruthers, John A. Ferguson, Priscilla E. Dombek, and Michael J. Sadowsky. "Sample Size, Library Composition, and Genotypic Diversity among Natural Populations of Escherichia coli from Different Animals Influence Accuracy of Determining Sources of Fecal Pollution." Applied and Environmental Microbiology 70, no. 8 (2004): 4478–85. http://dx.doi.org/10.1128/aem.70.8.4478-4485.2004.

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ABSTRACT A horizontal, fluorophore-enhanced, repetitive extragenic palindromic-PCR (rep-PCR) DNA fingerprinting technique (HFERP) was developed and evaluated as a means to differentiate human from animal sources of Escherichia coli. Box A1R primers and PCR were used to generate 2,466 rep-PCR and 1,531 HFERP DNA fingerprints from E. coli strains isolated from fecal material from known human and 12 animal sources: dogs, cats, horses, deer, geese, ducks, chickens, turkeys, cows, pigs, goats, and sheep. HFERP DNA fingerprinting reduced within-gel grouping of DNA fingerprints and improved alignment
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Cameron1, Cortney. "Species Richness of Cypress Dome Vegetation in West-Central Florida, USA." Wetland Science & Practice 41, no. 2 (2023): 51–56. http://dx.doi.org/10.1672/ucrt083-51.

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Cypress domes are relatively small forested depressional wetlands common in the southeastern United States. The vegetative species richness of cypress domes is quantified using 15 years of annual vegetation data for 41 relatively unimpacted cypress domes in west-central Florida. Wetland species richness was normally distributed, with a median of 73 species and standard deviation of 16 species. Across the sample, 396 species representing 204 genera and 92 families were observed, with the jackknife estimator predicting a species richness of 516, much higher than previous observed or predicted va
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Prakash, Mithilesh, Jaakko K. Sarin, Lassi Rieppo, Isaac O. Afara, and Juha Töyräs. "Optimal Regression Method for Near-Infrared Spectroscopic Evaluation of Articular Cartilage." Applied Spectroscopy 71, no. 10 (2017): 2253–62. http://dx.doi.org/10.1177/0003702817726766.

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Near-infrared (NIR) spectroscopy has been successful in nondestructive assessment of biological tissue properties, such as stiffness of articular cartilage, and is proposed to be used in clinical arthroscopies. Near-infrared spectroscopic data include absorbance values from a broad wavelength region resulting in a large number of contributing factors. This broad spectrum includes information from potentially noisy variables, which may contribute to errors during regression analysis. We hypothesized that partial least squares regression (PLSR) is an optimal multivariate regression technique and
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Chang, Chin-Chun, and Shen-Huan Chou. "Tuning of the hyperparameters for L2-loss SVMs with the RBF kernel by the maximum-margin principle and the jackknife technique." Pattern Recognition 48, no. 12 (2015): 3983–92. http://dx.doi.org/10.1016/j.patcog.2015.06.017.

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McRoberts, Ronald E., Steen Magnussen, Erkki O. Tomppo, and Gherardo Chirici. "Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data." Remote Sensing of Environment 115, no. 12 (2011): 3165–74. http://dx.doi.org/10.1016/j.rse.2011.07.002.

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I, Sulaiman, Aayushi S. Shetty, Abhishek Bharat, and A. K. Vijay Krishna Kumar. "Effectiveness Of Jackknife Stretching On Hamstring Tightness With Low Back Pain Among Information Technology Professionals - Experimental Study." IOSR Journal of Sports and Physical Education 11, no. 5 (2024): 01–06. http://dx.doi.org/10.9790/6737-1105010106.

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Background: Hamstring muscles are located at the back of the thigh and the primary action of hamstring muscles is flexion of the knee. It is an effective self-stretching technique; it combines static and dynamic stretching and can be performed without any equipment. Methods: For Jack-knife stretching, participants started in a full squat position, gripping both ankles. The subjects were instructed to extend their knees as much as possible while bringing their chest close to their thighs, holding this position for 10 seconds before returning to the starting position6 . This sequence was repeate
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Chen, Wei, Hao Lv, Fulei Nie, and Hao Lin. "i6mA-Pred: identifying DNA N6-methyladenine sites in the rice genome." Bioinformatics 35, no. 16 (2019): 2796–800. http://dx.doi.org/10.1093/bioinformatics/btz015.

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Abstract Motivation DNA N6-methyladenine (6mA) is associated with a wide range of biological processes. Since the distribution of 6mA site in the genome is non-random, accurate identification of 6mA sites is crucial for understanding its biological functions. Although experimental methods have been proposed for this regard, they are still cost-ineffective for detecting 6mA site in genome-wide scope. Therefore, it is desirable to develop computational methods to facilitate the identification of 6mA site. Results In this study, a computational method called i6mA-Pred was developed to identify 6m
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Wrobel, Gabriel D., Marie E. Danforth, and Carl Armstrong. "ESTIMATING SEX OF MAYA SKELETONS BY DISCRIMINANT FUNCTION ANALYSIS OF LONG-BONE MEASUREMENTS FROM THE PROTOHISTORIC MAYA SITE OF TIPU, BELIZE." Ancient Mesoamerica 13, no. 2 (2002): 255–63. http://dx.doi.org/10.1017/s0956536102132044.

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Discriminant functions were developed using long-bone robusticity measurements of 82 individuals from the protohistoric Maya site of Tipu, Belize. All individuals were sexed using nonmetric morphological indicators, particularly those of the pelvis. These functions are designed to provide a means of determining the sex of fragmentary prehistoric Maya skeletons. The equations ranged in accuracy from 77.5% to 100%. The reliability of these equations was tested using a jackknife method on the Tipu sample and by applying the equations to small samples of prehistoric skeletons from the sites of Sei
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Yang, Huan, Hua Tang, Xin-Xin Chen, et al. "Identification of Secretory Proteins inMycobacterium tuberculosisUsing Pseudo Amino Acid Composition." BioMed Research International 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/5413903.

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Tuberculosis is killing millions of lives every year and on the blacklist of the most appalling public health problems. Recent findings suggest that secretory protein ofMycobacterium tuberculosismay serve the purpose of developing specific vaccines and drugs due to their antigenicity. Responding to global infectious disease, we focused on the identification of secretory proteins inMycobacterium tuberculosis. A novel method calledMycoSecwas designed by incorporatingg-gap dipeptide compositions into pseudo amino acid composition. Analysis of variance-based technique was applied in the process of
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Lahiri, Kajal, Chuanming Gao, and Bernard Wixon. "Value of Sample Separation Information in a Sequential Probit Model." Arthaniti: Journal of Economic Theory and Practice 19, no. 2 (2020): 151–76. http://dx.doi.org/10.1177/0976747919900040.

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We illustrate the estimation and identification of multi-step sequential probit models with and without stepwise sample separation information. The likelihood functions are explicitly derived to ease experimentation with such models. We used data on health, activity limitations, demographic traits and work from the Survey of Income and Program Participation (SIPP) and exactly matched them with Social Security administrative records to showcase our theoretical points. Using a Monte Carlo simulation technique, our results suggest that the correlations in errors across equations may arise due to
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Ma, Liang, Hailin Jiang, Wanli Yang, and Quanjie Zhu. "A Novel Method to Identify Golgi Protein Types Based on Hybrid Feature and SVM Algorithm." International Journal of Computational Intelligence and Applications 19, no. 04 (2020): 2050027. http://dx.doi.org/10.1142/s1469026820500273.

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Accurate identification of Golgi protein types can provide useful clues to reveal the correlation between GA dysfunction and disease pathology and improve the ability to develop more effective treatments for the diseases. This paper introduces an effective and robust method to classify Golgi protein type with traditional machine learning algorithms. In which various features such as n-GDip, DCCA, psePSSM were used as training features and SVM with linear kernel was employed as a classifier. To solve the imbalance problem of the benchmark datasets, the oversampling technique SMOTE was adopted.
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Garcia, Xavier, and Alan G. Jones. "Robust processing of magnetotelluric data in the AMT dead band using the continuous wavelet transform." GEOPHYSICS 73, no. 6 (2008): F223—F234. http://dx.doi.org/10.1190/1.2987375.

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The energy sources for magnetotellurics (MT) at frequencies above [Formula: see text] are electromagnetic waves generated by distant lightning storms propagating globally within the earth-ionosphere waveguide. The nature of the sources and properties of this waveguide display diurnal and seasonal variations that can cause significant signal amplitude attenuation, especially at [Formula: see text] frequencies — the so-called audiomagnetotelluric (AMT) dead band. This lack of energy results in unreliable MT response estimates; and, given that in crystalline environments ore bodies located at som
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Fahira, Novita Sheisariana, and Nusar Hajarisman. "Penerapan Metode Penduga Area Kecil untuk Menduga Jumlah Pengangguran di Provinsi Jawa Barat Tahun 2020 dengan Model Poisson Gamma." Bandung Conference Series: Statistics 2, no. 2 (2022): 449–53. http://dx.doi.org/10.29313/bcss.v2i2.4717.

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Abstract. Small Area Estimation (SAE) is a statistical technique used to estimate the parameters of a small area. One of the SAE methods is Empirical Bayes (EB), where this method is used for binary or count data whose parameter estimators are more influenced by information from the data due to lack of information to determine the prior distribution. One application of the Empirical Bayes method is the Poisson-Gamma model. The purpose of this study is to estimate a small area of unemployment in West Java Province in 2020 using the empirical Bayes method based on the Poisson-Gamma model and to
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