On 16/10/16 04:24, mviljamaa wrote:
My conception of prediction intervals is the following:"a prediction interval gives an interval within which we expect next y_i to lie with a specified probability" So when using predict() for my model: predict(fit4, interval="prediction")[1:20,] I get: fit lwr upr 1 491.1783 381.3486 601.0081 2 515.4883 405.7128 625.2638 3 581.5957 447.9569 715.2344 4 522.4979 412.5086 632.4872 5 604.6008 492.2796 716.9221 6 520.2881 410.3108 630.2655 7 620.7379 507.9045 733.5713 8 621.0925 505.8731 736.3119 9 527.1810 417.2760 637.0859 10 519.4651 406.1622 632.7680 11 622.0051 512.0082 732.0021 12 536.6924 424.3415 649.0434 13 504.8618 394.9034 614.8202 14 545.5920 433.6530 657.5309 15 475.6153 362.4383 588.7923 16 462.5341 350.6090 574.4593 17 559.0888 448.1212 670.0564 18 544.0051 432.0583 655.9519 19 471.1450 355.2377 587.0523 20 604.3028 470.6925 737.9130 Now since the prediction interval gives the interval within which the _next_ y_i will fall, then how to read the above results? Does the previous row's "lwr" and "upr" refer to the next row's "fit"'s interval?
(a) This is really off-topic since it's more of a statistics question than an R question.
(b) Your understanding of prediction intervals is incorrect and confused. A 95% (for example) prediction interval will contain a *new* independent observation of y, at the same predictor value(s) with probability 0.95. Get your hands on an elementary statistics textbook and read it!
cheers, Rolf Turner -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276 ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
