On Performance of Acceptance Sampling Plans Using Sequential Probability Ratio Test Based on Truncated Life Tests Using Some Distribution Function

Zoramawa, Aminu Bello; DAURAN, N. S.; USMAN, H.; SYLVESTER, IBRAHIM

doi:10.33003/fjs-2022-0606-1131

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…We consider week index for PHASE1 of system test data for exposure time cumulative system test hours from the software reliability model with time dependent fault detection and fault removal Mengmeng & Hoang. We are going to consider the sample of 14week index out of 21week index and take the average life truncated hours of 2492 [11][12][13][14][15][16][17][18].…”

Section: Resultsmentioning

confidence: 99%

Modified Sequential Probability Ratio Test Based on Truncated Life Tests on the Exponential Distribution Functions

Sylvester,

2023

J Phy Math & its Appli

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Modified Sequential probability ratio test (MSPRT) technique helps to increase the reliability and speed of stabilization detection on the Non homogenous poison process (NHPP) with the maximum number of software faults to reduce error between the consumer risk and producer risk, with the time cumulative system of hours. Modified sequential probability ratio test can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of significance and power. The proposed result suggests MSPRT along with maximum number of faults contained in software would be useful in speeding up decision making while dealings error in a software reliability weekly index, we show the graphical performance of the MSPRT and average sample number (ASN).

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Section: Resultsmentioning

confidence: 99%

Modified Sequential Probability Ratio Test Based on Truncated Life Tests on the Exponential Distribution Functions

Sylvester,

2023

J Phy Math & its Appli

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“…However, there are three reasons why this is not the case. First, this study assumes that truncation such as in [30], [31] is not conducted, so the maximum sample number max(𝑁 𝑠 ) is not known in advance. Secondly, the amount of memory space 𝑀 to store the inverse matrices will depend on the random max(𝑁 𝑠 ).…”

Section: B Recursive Sequential Detector (Proposed Method)mentioning

confidence: 99%

Sequential Detection under Correlated Observations using Recursive Method

Suratman,

Istiqomah,

Rahmawati

2024

Jurnal Teknik Elektro

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Sequential analysis has been used in many cases when the decision is supposed to be taken quickly such as for signal detection in statistical signal processing, namely sequential detector. For identical error probabilities, a sequential detector needs a smaller average sample number (ASN) than its counterpart of a fixed sample number quadrature detector based on Neyman-Pearson criteria. The optimum sequential detector was derived based on the assumption that the observations are uncorrelated (independent). However, in realistic scenario, such as in radar, the assumption is commonly violated. Using a sequential detector under correlated observations is sub-optimal and it poses a problem. It demands a high computational complexity, since it needs to recalculate the inverse and the determinant of the signal covariance matrix for each new sample taken. This paper presents a technique for reducing the computational complexity, which involves using recursive matrix inverse to subsequently calculate conditional probability density functions (pdf). This eliminates the need to recalculate the inverse and determinant, leading to a more reasonable solution in real-world scenario. We evaluate the performance of the proposed (recursive) sequential detector by using Monte-Carlo simulations and we use the conventional and non-recursive sequential detectors for comparisons. The results show that the recursive sequential detector has equal probabilities of false alarm and miss-detection with the conventional sequential detector and performs better than the non-recursive sequential detector. In terms of ASN, it maintains comparable results to the two conventional detectors. The recursive approach has reduced the computational complexity for matrix multiplication to from and it also has rendered the calculation of matrix determinant to be unnecessary. Therefore, by having better probabilities of error and reduced computational complexities under correlated observations, the proposed recursive sequential detector may become a viable alternative to obtain a more agile detection system as required in future applications, such as in radar and cognitive radio.

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“…The ASPs focusing on the truncated lifetime tests are considered in literature by many researchers in many cases. See, for example, a list of applications with the corresponding references: the Tsallis q -exponential distribution, 3 the generalized exponential and exponential distributions, 4 , 5 the generalized inverted exponential distribution, 6 the weighted exponential distribution, 7 the three-parameter Kappa distribution, 8 the Birnbaum Saunders model, 9 the Garima distribution, 10 the transmuted generalized inverse Weibull distribution, 11 the extended Exponential distribution, 12 the new Weibull-Pareto distribution, 13 finite and infinite lot size under power Lindley distribution, 14 double ASP based on truncated life tests for the inverse Rayleigh distribution, 15 double ASP based on the Burr type X distribution, 16 the generalized inverse Weibull distribution, 17 the transmuted inverse Rayleigh distribution, 18 the Sushila distribution, 19 double ASP for transmuted generalized inverse Weibull distribution, 20 the generalized exponential distribution, 21 the Weibull product distribution, 22 the Gamma distribution, 23 the log-logistic model, 24 the inverse-gamma distribution, 25 ASP for Akash distribution, 26 length-biased weighted Lomax distribution, 27 three-parameter Lindley distribution, 28 double ASP for Half-Normal distribution, 29 and exponentiated generalized inverse Rayleigh distribution. 30 Also, see a mixed double sampling plan based on Cpk, 31 design of variables sampling plans based on the lifetime-performance index in the presence of hybrid censoring scheme, 32 determination of multiple dependent state repetitive group sampling plan based on the process capability index, 33 and selecting better process based on difference statistic using doubl...…”

Section: Introductionmentioning

confidence: 99%

Acceptance sampling plans under two-parameter Quasi Shanker distribution assuring mean life with an application to manufacturing data

2021

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The acceptance sampling plan (ASP) is a statistical tool used in industry for quality control to determine the quality of products by selecting a specified number for testing in order to accept or reject the lot. The main objective is to develop a new ASP based on truncated life tests assuming that the lifetime follows the two parameters Quasi Shanker distribution, since this distribution showed its superiority in providing a better model for some applications than the exponential distribution. The ASP steps are carried out to find the minimum sample sizes needed to assert the certain life mean that are calculated under a given customer’s risk. The operating characteristic values of the sampling plan and the producer risk values are obtained. The efficiency of the suggested plans is analyzed based on real data that is fitted to the Quasi Shanker distribution. For various values of the Quasi Shanker distribution parameters, numerical examples are presented for illustrative purposes. The results indicate that the suggested ASP provides smaller sample sizes than other competitors considered in this study. The suggested ASP has been found to provide a substantial sampling economy in terms of reducing the sample. Hence, it is recommended that the ASP can be used in industry and for future research works as double and group ASP.

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On Performance of Acceptance Sampling Plans Using Sequential Probability Ratio Test Based on Truncated Life Tests Using Some Distribution Function

Cited by 3 publications

References 34 publications

Modified Sequential Probability Ratio Test Based on Truncated Life Tests on the Exponential Distribution Functions

Modified Sequential Probability Ratio Test Based on Truncated Life Tests on the Exponential Distribution Functions

Sequential Detection under Correlated Observations using Recursive Method

Acceptance sampling plans under two-parameter Quasi Shanker distribution assuring mean life with an application to manufacturing data

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