. Neyman and E. S. Pearson. "On the problem of the most efficient tests of statistical hypotheses". Phil. Trans. Roy. Soc., Ser. A., 231:289--337, 1933.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....set of sensor decisions u = u 1 ; uN ) We let fl k (x k ) denote the probability we decide for U k = 1 for a given observation x k . A complete set of sensor rules and fusion rule are described by fl = fl 0 ; fl 1 ; fl N ) Let us focus on the Neyman Pearson (NP) criterion [13, 14, 15]. Specifically, denote the problem of interest as NP which is defined as finding a fl that satisfies NP : max fl P d (fl) subject to the constraint P f (fl) ff where P d (fl) P rob(U 0 = 1jH 1 ) is the probability of detection obtained when fl is used, P f (fl) P rob(U 0 = 1jH 0 ) is ....

J. Neyman, and E. Pearson, "On the problem of the most efficient tests of statistical hypotheses," Philosophical Transactions of the Royal Society of London, A231, 9, pp. 289-337, Feb. 1933. 107

....of signal detection and estimation deals with the processing of information bearing signals in order to make inferences about the information that they contain. Although this field clearly traces its provenance to the classical work of Bayes [6] Gauss [31] Fisher [27] and Neyman and Pearson [76] on statistical inference, 1 it was not until after the mathematical stage was set in the 1930 s by the pioneers of stochastic processes Kolmogorov, L evy, Wiener, and others that the field took hold as a recognizable discipline. Moreover, the possibilities for implementing any more than the ....

.... natural criterion for the detection problem, the connection to statistical hypothesis testing was perhaps first made by the distinguished mathematician, Mark Kac, who used to joke that his major contribution to the war effort was to provide a reference to the classic paper of Neyman and Pearson [76]. The Neyman Pearson criterion seeks a receiver that would maximize the probability of correct detection while keeping the probability of false alarm less than a specified value, a very appropriate criterion for radar. The theory shows that the key quantity to compute is the likelihood ratio ....

J. Neyman and E. Pearson, "On the problem of the most efficient tests of statistical hypotheses," Phil. Trans. Roy. Soc., vol. A 231, no. 9, pp. 492--510, 1933.

....diagnosers be correct. In our experience, a diagnostic design is generally correct under assumptions restricting the failures that can occur in the plant. Nevertheless it is important to understand the existence and computation of such solutions. Note the similarities to the NeymannPearson problem [8]. This problem is deterministic. Therefore unlike the Neymann Pearson problem languages with type one or type two errors cannot be compared in terms of false alarm and misdetection probabilities. Nevertheless in practise detecting languages with false alarms are a useful concept. Like the ....

J. Neyman and E. S. Pearson. On the problem of the most efficient tests of statistical hypotheses. Phil. Trans. Roy. Soc., Ser. A., 231:289--337, 1933.

....and Computer Science Department, Lehigh University, Bethlehem, PA 18015 y This paper is based on work supported by the Office of Naval Research under Grant No. N00014 97 10774 and by the National Science Foundation under Grant No. MIP 9703730 1 1 Introduction The Neyman Pearson criterion [1, 2] is fundamental to the development of the theory of hypothesis testing in the statistics and engineering literature [3, 4] It has emerged as the criterion of choice for many surveillance system applications, including radar system applications [5] More recently distributed hypothesis testing ....

J. Neyman, and E. Pearson, "On the problem of the most efficient tests of statistical hypotheses," Philosophical Transactions of the Royal Society of London, A231, 9, pp. 289-337, Feb. 1933. 18

....set comparisons into an equivalent number of Bernoulli trials as described above. Moreover, through this expression of the decision processes as an ensemble of elementary yes no questions, the different biometrics would all acquire the benefits 9 Phase Quadrant Iris Demodulation Code [0, 0] [1, 0] [1, 1] 0, 1] Re Im Figure 5: Iris encoding by phase demodulation with complex valued 2D Gabor wavelets. of having factorial (binomial class) tails, i.e. rapidly attenuating densities, instead of exponential or flatter ones. This in turn would facilitate the execution of decision making by a ....

....comparisons into an equivalent number of Bernoulli trials as described above. Moreover, through this expression of the decision processes as an ensemble of elementary yes no questions, the different biometrics would all acquire the benefits 9 Phase Quadrant Iris Demodulation Code [0, 0] 1, 0] [1, 1] [0, 1] Re Im Figure 5: Iris encoding by phase demodulation with complex valued 2D Gabor wavelets. of having factorial (binomial class) tails, i.e. rapidly attenuating densities, instead of exponential or flatter ones. This in turn would facilitate the execution of decision making by a simple ....

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J. Neyman and E.S. Pearson, "On the problem of the most efficient tests of statistical hypotheses, " Phil. Trans. Roy. Soc. London, Series A, Vol. 231, 1933, pp. 289-337.

....H 0 j H 0 trueg and fi = Pf accept H 0 j H 0 falseg. Since the minimization of all three quantities yields conflicting goals, two parameters must be fixed while the third one is minimized. Under the scenario to test a simple hypothesis against another simple hypothesis optimal tests are known. Neyman and Pearson (1933) have developed a method to construct statistical tests such that the error probability fi is minimized for given ff and sample size n. Another type of optimality is associated with the sequential probability ratio test (SPRT) developed by Abraham Wald (1945) This test is of sequential nature ....

Neyman, J. and E. S. Pearson (1933). On the problem of the most efficient tests of statistical hypotheses.

....statistics educators provide, and scientific journals rigidly adhere to, is to choose ff to be 0.05 or 0.01, regardless of sample size. These particular ff levels arose in Sir Ronald Fisher s study of relatively small agricultural experiments (on the order of 30 200 plots) Textbook advice (e.g. Neyman and Pearson, 1933) has emphasized the need to take account of the power of the test against HA when setting ff, and somehow reduce ff when the sample size is large. This crucial but vague advice has largely fallen on deaf ears. 2. Raftery (1995) points out that the whole hypothesis testing framework rests on the ....

Neyman, J. and Pearson, E.S. 1933. On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society (Series A) 231:289--337.

No context found.

. Neyman and E. S. Pearson. "On the problem of the most efficient tests of statistical hypotheses". Phil. Trans. Roy. Soc., Ser. A., 231:289--337, 1933.

No context found.

Neyman, J., Pearson, E.S., "On the Problem of the Most Efficient Tests of Statistical Hypotheses," Philosophical Transactions of the Royal Society, Series A, Vol. 231, 1933, pp. 289-337.

No context found.

Neyman, J., and Pearson, E.S., "On the Problem of the Most Efficient Tests of Statistical Hypotheses," Philosophical Transactions of the Royal Society, Series A, Vol. 231, 1933, pp. 289-337.

No context found.

J. Neyman and E. Pearson, "On the problem of the most efficient tests of statistical hypotheses," Phil. Trans. Roy. Soc., vol. A 231, no. 9, pp. 492--510, 1933.

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