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two new samples (521 students and 328 adults). Again, the scales showed impressive convergent validity, with correlations ranging from .77 to .89 across the two samples. Moreover, consistent with the Table 14.2 results, the correlation between the Fear and Sadness scales of the PANAS-X was signi cantly lower (.58 and .59 in the student and adult data, respectively) than that between POMS Tension-Anxiety and Depression-Dejection (r = .69 and .69, respectively) in both samples. We badly need further comparative data of this sort, representing a much broader array of scales, instruments, time instructions, and participants. In the absence of such data, it is impossible to offer any de nitive evaluation of the relative psychometric adequacy of these various mood inventories. With such data, however, we nally could begin to resolve some of the measurement differences we have noted and, consequently, move assessment in this area forward.



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Lapidoth, A., xxi, 707 Laplace, P.S., 488, 489 Laplace distribution, 257, 661 Laplace estimate, 488 large deviation theory, 4, 12, 357, 360 Latan , H.A., 182, 655, 707 e Lavenberg, S., xxiii law of large numbers, 57, 199, 245, 267, 319, 326, 355 357, 361, 403, 477, 479, 520, 522, 615 incompressible sequences, 477, 502 method of types, 355 weak law, 57, 58, 65, 196, 245, 361, 380, 479 lecturer, 561 Lee, E.A., 707 Leech, J., 707 Lehmann, E.L., 56, 707 Leibler, R.A., 55, 707 Lempel, A., 428, 442, 462, 707, 721, see also Lempel-Ziv coding Lempel-Ziv, xed database, 459 in nite dictionary, 458 sliding window, 443 tree structured, 448 Lempel-Ziv algorithm, xxiii, 441 Lempel-Ziv coding, 440 456 Lempel-Ziv compression, 360 Lempel-Ziv parsing, 427 letter, 105, 168 171, 174, 175, 209, 210, 224, 226, 233 Leung, C.S.K., 593, 609, 610, 696, 711 Levin, L.A., 507, 707 Levinson algorithm, 419 Levy s martingale convergence theorem, 647 lexicographic order, 327, 472 Li, M., 508, 707 Liao, H., 10, 609, 708 liar paradox, 483 Lieb, E.J., 693 likelihood, 20, 365, 377, 404, 482, 508 likelihood ratio, 482 likelihood ratio test, 377, 378, 385, 389 Lin, S., 708 Lind, D., 708 Linde, Y., 708





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[20] TeleManagement Forum: Enhanced Telecom Operations Map (eTOM), The Business Process Framework . TMF approved version 4.0, March 2004. [21] TeleManagement Forum: Shared Information/Data (SID) Model: Concepts, Principles, and Business Entities GB922 . TMF approved version 3.0, July 2003. [22] The Parlay Group Speci cations. Online: www.parlay.org. [23] van der Aalst W.M.P.: The Application of Petri Nets to Work ow Management . Journal of Circuits, Systems and Computers, Vol. 8, No. 1, pp. 21 66, 1998. [24] W3C: RDF Primer . W3C Recommendation, February 2004. [25] Wagner M. (ed.): Final Report about Ubiquitous Mobile Applications and Services: Including updated speci cation for context management technologies . IST-MobiLife Project Deliverable D32 (D4.6), December 2006. Online: www.ist-mobilife.org.

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D1 z1 1; t 2; 3; . . . where Dt zt is the density of the data evaluated around the last data point of the data stream provided to the algorithm zt ; n denotes the dimension of the inputs vector; m is the dimension of the outputs vector; and t denotes the number of points for which information about z is available. In eClustering the density, Dt zt is evaluated recursively and the whole information that concerns the spatial distribution of all data is accumulated in a small number (n m 1) of variables (bt and ctj ; j 1; n m ): Dt zt t 1 t 1 ! z2 1 bt 2 tj

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by the lowercase letter a and a subscript: a1 denotes one diet and a2 denotes the other. A particular but unspeci ed level of treatment A is denoted by aj, where j ranges over the values 1 and 2. The amount of weight loss in pounds 2 months after participant i went on diet j is denoted by Yij. The null and alternative hypotheses for the weight-loss experiment are, respectively, H0: H1:

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