Hi, I'm not very clear on what you are trying to achieve, but I think you could try the following for your Q1...
> Q1: Please how do I generate many samples as x above, say up to 5000 > or 10,000? I manually generated and stored as x1,x2, x3 up to x100. ndta = nrow(dta) x0 = 8890 x1 = 9500 xx = seq(from = x0, to = x1, by = 1) N_many = 50 # make 5000 etc as required m <- sapply( seq_len(N_many), function(i) sample(xx, ndta, replace = TRUE)) str(m) # int [1:1136, 1:50] 9147 8904 9062 8946 9330 9056 9239 9284 9290 9441 ... summary(as.vector(m)) # Min. 1st Qu. Median Mean 3rd Qu. Max. # 8890 9043 9195 9196 9348 9500 m[1:5, 1:5] # [,1] [,2] [,3] [,4] [,5] #[1,] 9147 9124 9341 8999 9268 #[2,] 8904 9246 9087 9041 8943 #[3,] 9062 9184 9061 9119 9350 #[4,] 8946 9242 8932 9306 9270 #[5,] 9330 8979 9437 9030 9333 Each sample set of length ndta (in this case ndta = 1136) is found in a column of the matrix. Is that what you are looking for? Ben > On Feb 27, 2019, at 4:53 PM, Ogbos Okike <giftedlife2...@gmail.com> wrote: > > Dear Kind List, > > I am still battling with this. I have, however, made some progress > with the suggestions of Micheal and others. At least, I have a better > picture of what I want to do now as I will attempt a detailed > description here. > > I am aware I should show you just a small part of my code and data. > But when I copied out a small portion and run to see what you get when > I send that, I was not satisfied with the signal displayed. The epoch > analysis averages data and is quite sensitive to leveraging, > especially if a small sample is used. > > So please permit/exercise patience me to display the series of epoch > that give the averaged valued used. You can just run the code and see > the signal of interest. Here is the code and the data: > > dta <- read.table( text ="n CR > -5 8969 > -4 8932 > -3 8929 > -2 8916 > -1 8807 > 0 8449 > 1 8484 > 2 8148 > 3 8282 > 4 8305 > 5 8380 > 6 8530 > 7 8642 > 8 8780 > 9 8890 > 10 8962 > -5 8929 > -4 8916 > -3 8807 > -2 8449 > -1 8484 > 0 8148 > 1 8282 > 2 8305 > 3 8380 > 4 8530 > 5 8642 > 6 8780 > 7 8890 > 8 8962 > 9 8949 > 10 8974 > -5 8744 > -4 8786 > -3 8828 > -2 8807 > -1 8716 > 0 8520 > 1 8634 > 2 8640 > 3 8636 > 4 8658 > 5 8699 > 6 8682 > 7 8621 > 8 8626 > 9 8660 > 10 8737 > -5 8592 > -4 8612 > -3 8628 > -2 8589 > -1 8318 > 0 8264 > 1 8294 > 2 8410 > 3 8442 > 4 8416 > 5 8389 > 6 8412 > 7 8453 > 8 8563 > 9 8581 > 10 8613 > -5 8264 > -4 8294 > -3 8410 > -2 8442 > -1 8416 > 0 8389 > 1 8412 > 2 8453 > 3 8563 > 4 8581 > 5 8613 > 6 8647 > 7 8613 > 8 8508 > 9 7829 > 10 7499 > -5 8613 > -4 8647 > -3 8613 > -2 8508 > -1 7829 > 0 7499 > 1 8213 > 2 7993 > 3 7821 > 4 8316 > 5 8460 > 6 8533 > 7 8584 > 8 8586 > 9 8567 > 10 8573 > -5 8508 > -4 7829 > -3 7499 > -2 8213 > -1 7993 > 0 7821 > 1 8316 > 2 8460 > 3 8533 > 4 8584 > 5 8586 > 6 8567 > 7 8573 > 8 8617 > 9 8591 > 10 8661 > -5 8851 > -4 8893 > -3 8858 > -2 8803 > -1 8790 > 0 8468 > 1 8545 > 2 8570 > 3 8568 > 4 8624 > 5 8669 > 6 8236 > 7 8190 > 8 8313 > 9 8389 > 10 8421 > -5 8803 > -4 8790 > -3 8468 > -2 8545 > -1 8570 > 0 8568 > 1 8624 > 2 8669 > 3 8236 > 4 8190 > 5 8313 > 6 8389 > 7 8421 > 8 8468 > 9 8537 > 10 8580 > -5 8570 > -4 8568 > -3 8624 > -2 8669 > -1 8236 > 0 8190 > 1 8313 > 2 8389 > 3 8421 > 4 8468 > 5 8537 > 6 8580 > 7 8605 > 8 8646 > 9 8690 > 10 8770 > -5 8690 > -4 8770 > -3 8799 > -2 8821 > -1 8666 > 0 8539 > 1 8633 > 2 8617 > 3 8651 > 4 8693 > 5 8715 > 6 8738 > 7 8716 > 8 8677 > 9 8680 > 10 8700 > -5 8756 > -4 8632 > -3 8662 > -2 8596 > -1 8552 > 0 8502 > 1 8633 > 2 8702 > 3 8745 > 4 8730 > 5 8708 > 6 8817 > 7 8724 > 8 8688 > 9 8693 > 10 8746 > -5 8926 > -4 8888 > -3 8798 > -2 8651 > -1 8678 > 0 8578 > 1 8593 > 2 8598 > 3 8526 > 4 8181 > 5 8204 > 6 8373 > 7 8599 > 8 8773 > 9 8784 > 10 8746 > -5 8678 > -4 8578 > -3 8593 > -2 8598 > -1 8526 > 0 8181 > 1 8204 > 2 8373 > 3 8599 > 4 8773 > 5 8784 > 6 8746 > 7 8747 > 8 8757 > 9 8749 > 10 8767 > -5 8757 > -4 8749 > -3 8767 > -2 8754 > -1 8695 > 0 8631 > 1 8661 > 2 8653 > 3 8588 > 4 8562 > 5 8613 > 6 8595 > 7 8498 > 8 8404 > 9 8507 > 10 8599 > -5 8695 > -4 8631 > -3 8661 > -2 8653 > -1 8588 > 0 8562 > 1 8613 > 2 8595 > 3 8498 > 4 8404 > 5 8507 > 6 8599 > 7 8592 > 8 8600 > 9 8637 > 10 8635 > -5 8588 > -4 8562 > -3 8613 > -2 8595 > -1 8498 > 0 8404 > 1 8507 > 2 8599 > 3 8592 > 4 8600 > 5 8637 > 6 8635 > 7 8632 > 8 8674 > 9 8644 > 10 8687 > -5 8595 > -4 8498 > -3 8404 > -2 8507 > -1 8599 > 0 8592 > 1 8600 > 2 8637 > 3 8635 > 4 8632 > 5 8674 > 6 8644 > 7 8687 > 8 8721 > 9 8747 > 10 8748 > -5 8599 > -4 8592 > -3 8600 > -2 8637 > -1 8635 > 0 8632 > 1 8674 > 2 8644 > 3 8687 > 4 8721 > 5 8747 > 6 8748 > 7 8739 > 8 8763 > 9 8792 > 10 8558 > -5 8600 > -4 8637 > -3 8635 > -2 8632 > -1 8674 > 0 8644 > 1 8687 > 2 8721 > 3 8747 > 4 8748 > 5 8739 > 6 8763 > 7 8792 > 8 8558 > 9 8442 > 10 8555 > -5 8748 > -4 8739 > -3 8763 > -2 8792 > -1 8558 > 0 8442 > 1 8555 > 2 8622 > 3 8634 > 4 8698 > 5 8732 > 6 8713 > 7 8732 > 8 8681 > 9 8615 > 10 8624 > -5 8698 > -4 8732 > -3 8713 > -2 8732 > -1 8681 > 0 8615 > 1 8624 > 2 8649 > 3 8656 > 4 8678 > 5 8723 > 6 8693 > 7 8548 > 8 7803 > 9 7801 > 10 7724 > -5 8723 > -4 8693 > -3 8548 > -2 7803 > -1 7801 > 0 7724 > 1 7910 > 2 7829 > 3 7995 > 4 8156 > 5 8307 > 6 8377 > 7 8465 > 8 8506 > 9 8516 > 10 8536 > -5 8548 > -4 7803 > -3 7801 > -2 7724 > -1 7910 > 0 7829 > 1 7995 > 2 8156 > 3 8307 > 4 8377 > 5 8465 > 6 8506 > 7 8516 > 8 8536 > 9 8574 > 10 8623 > -5 8821 > -4 8856 > -3 8798 > -2 8772 > -1 8705 > 0 8682 > 1 8691 > 2 8720 > 3 8727 > 4 8789 > 5 8821 > 6 8811 > 7 8841 > 8 8849 > 9 8849 > 10 8860 > -5 8835 > -4 8829 > -3 8826 > -2 8799 > -1 8775 > 0 8756 > 1 8793 > 2 8814 > 3 8847 > 4 8838 > 5 8833 > 6 8841 > 7 8847 > 8 8903 > 9 8933 > 10 8918 > -5 8890 > -4 8875 > -3 8874 > -2 8865 > -1 8891 > 0 8839 > 1 8853 > 2 8888 > 3 8884 > 4 8890 > 5 8889 > 6 8839 > 7 8879 > 8 8908 > 9 8924 > 10 8882 > -5 8853 > -4 8888 > -3 8884 > -2 8890 > -1 8889 > 0 8839 > 1 8879 > 2 8908 > 3 8924 > 4 8882 > 5 8910 > 6 8903 > 7 8859 > 8 8858 > 9 8863 > 10 8847 > -5 8924 > -4 8882 > -3 8910 > -2 8903 > -1 8859 > 0 8858 > 1 8863 > 2 8847 > 3 8883 > 4 8869 > 5 8878 > 6 8897 > 7 8922 > 8 8895 > 9 8858 > 10 8858 > -5 8910 > -4 8903 > -3 8859 > -2 8858 > -1 8863 > 0 8847 > 1 8883 > 2 8869 > 3 8878 > 4 8897 > 5 8922 > 6 8895 > 7 8858 > 8 8858 > 9 8736 > 10 8905 > -5 8859 > -4 8858 > -3 8863 > -2 8847 > -1 8883 > 0 8869 > 1 8878 > 2 8897 > 3 8922 > 4 8895 > 5 8858 > 6 8858 > 7 8736 > 8 8905 > 9 8935 > 10 8974 > -5 8897 > -4 8922 > -3 8895 > -2 8858 > -1 8858 > 0 8736 > 1 8905 > 2 8935 > 3 8974 > 4 8946 > 5 8952 > 6 9010 > 7 8980 > 8 8976 > 9 8970 > 10 8961 > -5 9376 > -4 9336 > -3 9311 > -2 9287 > -1 9221 > 0 9087 > 1 9132 > 2 9175 > 3 9166 > 4 9240 > 5 9264 > 6 9271 > 7 9319 > 8 9324 > 9 9333 > 10 9351 > -5 9287 > -4 9221 > -3 9087 > -2 9132 > -1 9175 > 0 9166 > 1 9240 > 2 9264 > 3 9271 > 4 9319 > 5 9324 > 6 9333 > 7 9351 > 8 9362 > 9 9385 > 10 9354 > -5 9407 > -4 9414 > -3 9354 > -2 9298 > -1 9319 > 0 9147 > 1 9178 > 2 9196 > 3 9258 > 4 9303 > 5 9369 > 6 9382 > 7 9375 > 8 9389 > 9 9376 > 10 9264 > -5 9386 > -4 9396 > -3 9424 > -2 9391 > -1 9284 > 0 9267 > 1 9278 > 2 9318 > 3 9334 > 4 9275 > 5 9306 > 6 9308 > 7 9358 > 8 9335 > 9 9373 > 10 9379 > -5 9284 > -4 9267 > -3 9278 > -2 9318 > -1 9334 > 0 9275 > 1 9306 > 2 9308 > 3 9358 > 4 9335 > 5 9373 > 6 9379 > 7 9355 > 8 9340 > 9 9327 > 10 9320 > -5 9327 > -4 9320 > -3 9315 > -2 9336 > -1 9371 > 0 9259 > 1 9330 > 2 9355 > 3 9334 > 4 9353 > 5 9370 > 6 9394 > 7 9400 > 8 9318 > 9 9037 > 10 8994 > -5 9394 > -4 9400 > -3 9318 > -2 9037 > -1 8994 > 0 8943 > 1 8964 > 2 8997 > 3 9158 > 4 8964 > 5 8564 > 6 8736 > 7 8818 > 8 8938 > 9 9034 > 10 9132 > -5 8943 > -4 8964 > -3 8997 > -2 9158 > -1 8964 > 0 8564 > 1 8736 > 2 8818 > 3 8938 > 4 9034 > 5 9132 > 6 9167 > 7 9200 > 8 9257 > 9 9266 > 10 9306 > -5 9338 > -4 9354 > -3 9372 > -2 9338 > -1 9308 > 0 9282 > 1 9324 > 2 9318 > 3 9342 > 4 9370 > 5 9331 > 6 9327 > 7 9338 > 8 9381 > 9 9394 > 10 9332 > -5 9372 > -4 9338 > -3 9308 > -2 9282 > -1 9324 > 0 9318 > 1 9342 > 2 9370 > 3 9331 > 4 9327 > 5 9338 > 6 9381 > 7 9394 > 8 9332 > 9 9331 > 10 9293 > -5 9338 > -4 9381 > -3 9394 > -2 9332 > -1 9331 > 0 9293 > 1 9309 > 2 9325 > 3 9406 > 4 9409 > 5 9413 > 6 9426 > 7 9440 > 8 9449 > 9 9512 > 10 9494 > -5 9361 > -4 9354 > -3 9299 > -2 9282 > -1 9250 > 0 9242 > 1 9254 > 2 9321 > 3 9390 > 4 9414 > 5 9435 > 6 9437 > 7 9426 > 8 9398 > 9 9383 > 10 9354 > -5 9365 > -4 9421 > -3 9416 > -2 9355 > -1 9338 > 0 9324 > 1 9325 > 2 9322 > 3 9319 > 4 9381 > 5 9315 > 6 9314 > 7 9359 > 8 9403 > 9 9419 > 10 9474 > -5 9355 > -4 9338 > -3 9324 > -2 9325 > -1 9322 > 0 9319 > 1 9381 > 2 9315 > 3 9314 > 4 9359 > 5 9403 > 6 9419 > 7 9474 > 8 9525 > 9 9501 > 10 9447 > -5 9325 > -4 9322 > -3 9319 > -2 9381 > -1 9315 > 0 9314 > 1 9359 > 2 9403 > 3 9419 > 4 9474 > 5 9525 > 6 9501 > 7 9447 > 8 9424 > 9 9396 > 10 9388 > -5 9447 > -4 9424 > -3 9396 > -2 9388 > -1 9396 > 0 9346 > 1 9358 > 2 9353 > 3 9350 > 4 9378 > 5 9372 > 6 9354 > 7 9349 > 8 9392 > 9 9440 > 10 9467 > -5 9388 > -4 9396 > -3 9346 > -2 9358 > -1 9353 > 0 9350 > 1 9378 > 2 9372 > 3 9354 > 4 9349 > 5 9392 > 6 9440 > 7 9467 > 8 9519 > 9 9550 > 10 9565 > -5 9353 > -4 9350 > -3 9378 > -2 9372 > -1 9354 > 0 9349 > 1 9392 > 2 9440 > 3 9467 > 4 9519 > 5 9550 > 6 9565 > 7 9565 > 8 9497 > 9 9500 > 10 9472 > -5 9522 > -4 9529 > -3 9492 > -2 9432 > -1 9382 > 0 9355 > 1 9361 > 2 9350 > 3 9382 > 4 9451 > 5 9491 > 6 9506 > 7 9529 > 8 9543 > 9 9556 > 10 9553 > -5 9492 > -4 9432 > -3 9382 > -2 9355 > -1 9361 > 0 9350 > 1 9382 > 2 9451 > 3 9491 > 4 9506 > 5 9529 > 6 9543 > 7 9556 > 8 9553 > 9 9502 > 10 9470 > -5 9551 > -4 9505 > -3 9389 > -2 9406 > -1 9377 > 0 9284 > 1 9365 > 2 9424 > 3 9412 > 4 9403 > 5 9384 > 6 9394 > 7 9404 > 8 9413 > 9 9407 > 10 9405 > -5 9579 > -4 9576 > -3 9543 > -2 9451 > -1 9421 > 0 9361 > 1 9394 > 2 9400 > 3 9387 > 4 9366 > 5 9346 > 6 9360 > 7 9385 > 8 9435 > 9 9443 > 10 9430 > -5 9361 > -4 9394 > -3 9400 > -2 9387 > -1 9366 > 0 9346 > 1 9360 > 2 9385 > 3 9435 > 4 9443 > 5 9430 > 6 9454 > 7 9531 > 8 9547 > 9 9581 > 10 9540 > -5 9510 > -4 9546 > -3 9564 > -2 9508 > -1 9422 > 0 9369 > 1 9395 > 2 9438 > 3 9423 > 4 9392 > 5 9368 > 6 9366 > 7 9348 > 8 9340 > 9 9375 > 10 9391 > -5 9423 > -4 9392 > -3 9368 > -2 9366 > -1 9348 > 0 9340 > 1 9375 > 2 9391 > 3 9466 > 4 9545 > 5 9574 > 6 9564 > 7 9527 > 8 9513 > 9 9494 > 10 9542 > -5 9511 > -4 9491 > -3 9457 > -2 9453 > -1 9402 > 0 9382 > 1 9407 > 2 9437 > 3 9403 > 4 9404 > 5 9425 > 6 9486 > 7 9457 > 8 9451 > 9 9423 > 10 9401 > -5 9425 > -4 9486 > -3 9457 > -2 9451 > -1 9423 > 0 9401 > 1 9429 > 2 9422 > 3 9431 > 4 9462 > 5 9475 > 6 9474 > 7 9487 > 8 9493 > 9 9495 > 10 9499 > -5 9404 > -4 9385 > -3 9363 > -2 9399 > -1 9411 > 0 9355 > 1 9357 > 2 9363 > 3 9382 > 4 9387 > 5 9408 > 6 9429 > 7 9456 > 8 9487 > 9 9526 > 10 9487 > -5 9493 > -4 9439 > -3 9400 > -2 9378 > -1 9371 > 0 9369 > 1 9374 > 2 9305 > 3 9298 > 4 9298 > 5 9325 > 6 9381 > 7 9477 > 8 9508 > 9 9496 > 10 9517 > -5 9371 > -4 9369 > -3 9374 > -2 9305 > -1 9298 > 0 9298 > 1 9325 > 2 9381 > 3 9477 > 4 9508 > 5 9496 > 6 9517 > 7 9561 > 8 9570 > 9 9546 > 10 9544 > -5 9510 > -4 9506 > -3 9530 > -2 9441 > -1 9427 > 0 9393 > 1 9420 > 2 9444 > 3 9468 > 4 9484 > 5 9525 > 6 9542 > 7 9557 > 8 9548 > 9 9550 > 10 9593 > -5 9589 > -4 9598 > -3 9527 > -2 9417 > -1 9390 > 0 9374 > 1 9386 > 2 9407 > 3 9453 > 4 9447 > 5 9419 > 6 9386 > 7 9373 > 8 9364 > 9 9376 > 10 9389 > -5 9453 > -4 9447 > -3 9419 > -2 9386 > -1 9373 > 0 9364 > 1 9376 > 2 9389 > 3 9376 > 4 9375 > 5 9370 > 6 9391 > 7 9458 > 8 9446 > 9 9456 > 10 9463 > -5 9364 > -4 9376 > -3 9389 > -2 9376 > -1 9375 > 0 9370 > 1 9391 > 2 9458 > 3 9446 > 4 9456 > 5 9463 > 6 9500 > 7 9486 > 8 9474 > 9 9495 > 10 9531 > -5 9491 > -4 9441 > -3 9388 > -2 9380 > -1 9369 > 0 9354 > 1 9367 > 2 9369 > 3 9341 > 4 9305 > 5 9308 > 6 9324 > 7 9385 > 8 9451 > 9 9496 > 10 9527 > -5 9369 > -4 9354 > -3 9367 > -2 9369 > -1 9341 > 0 9305 > 1 9308 > 2 9324 > 3 9385 > 4 9451 > 5 9496 > 6 9527 > 7 9544 > 8 9543 > 9 9535 > 10 9536 > -5 9586 > -4 9583 > -3 9572 > -2 9533 > -1 9454 > 0 9392 > 1 9420 > 2 9451 > 3 9475 > 4 9514 > 5 9561 > 6 9542 > 7 9502 > 8 9461 > 9 9468 > 10 9463 > -5 9587 > -4 9562 > -3 9530 > -2 9445 > -1 9404 > 0 9395 > 1 9417 > 2 9449 > 3 9467 > 4 9470 > 5 9524 > 6 9512 > 7 9448 > 8 9398 > 9 9431 > 10 9467 > -5 9467 > -4 9470 > -3 9524 > -2 9512 > -1 9448 > 0 9398 > 1 9431 > 2 9467 > 3 9490 > 4 9517 > 5 9526 > 6 9574 > 7 9573 > 8 9562 > 9 9563 > 10 9566 > ",header=TRUE) > > data<-matrix(c(dta$CR),ncol=71) > A<-matrix(rep(-5:10,71)) > B<-matrix(data) > > oodf<-data.frame(A,B) > a<--5:10 > oodf<-data.frame(A,B) > library(plotrix) > std.error<-function(x) return(sd(x)/(sum(!is.na(x)))) > oomean<-as.vector(by(oodf$B,oodf$A,mean)) > oose<-as.vector(by(oodf$B,oodf$A,std.error)) > plot(-5:10,oomean,type="l",ylim=c(8890,9100), > ) > A<-oomean-1.96*oose > B<-oomean+1.96*oose > lines(a,A,col="red") > lines(a,B,col="red") > > My Question: > I wish to conduct a randomization test of significance (90 and 99 > percentile) of the reductions/decreases as displayed by the signal. > > I am attempting using: > x<-sample(8890:9500,1136,replace=T ) > > to generate the random numbers, where 8890, 9500 and 1136 are the > minimum and maximum of the signal and 1136 the length of sample data. > Q1: Please how do I generate many samples as x above, say up to 5000 > or 10,000? I manually generated and stored as x1,x2, x3 up to x100. > > Q2: Please how do I use this randomly generated numbers to test the > statistical significance level of the signal generated by > plot(-5:10,oomean,type="l",ylim=c(8890,9100), )? > > I wish to test for 90% and 99% percentile. > > I am sorry that this is too long. > > Many thanks for your kind contributions > > Best > Ogbos > > > > > > > > On Sun, Feb 10, 2019 at 3:55 PM Ogbos Okike <giftedlife2...@gmail.com> wrote: >> >> Dear Michael, >> This is great! Thank you. >> >> I have not really got any response other than yours. >> >> I have long before now included what I have in a paper submitted to a >> journal. >> >> I am awaiting the feedback of the reviewer. I will compare the >> comments with your input here and determine the corrections to make >> and probably return to the list for additional help. >> >> Best wishes >> Ogbos >> >> On Fri, Feb 8, 2019 at 4:31 PM Meyners, Michael <meyner...@pg.com> wrote: >>> >>> Ogbos, >>> >>> You do not seem to have received a reply over the list yet, which might be >>> due to the fact that this seems rather a stats than an R question. Neither >>> got your attachment (Figure) through - see posting guide. >>> >>> I'm not familiar with epoch analysis, so not sure what exactly you are >>> doing / trying to achieve, but some general thoughts: >>> >>> * You do NOT want to restrict your re-randomizations in a way that "none of >>> the dates corresponds with the ones in the real event" - actually, as a >>> general principle, the true data must be an admissible re-randomization as >>> well. You seem to have excluded that (and a lot of other randomizations at >>> the same time which might have occurred, i.e. dates 1 and 2 reversed but >>> all others the same), thereby rendering the test invalid. Any restrictions >>> you have on your re-randomizations must've applied to the original >>> randomization as well. >>> * If you have rather observational data (which I suspect, but not sure), >>> Edgington & Onghena (2007) would rather refer to this as a permutation test >>> - the difference being that you have to make strong assumptions (similar to >>> parametric tests) on the nature of the data, which are designed-in to be >>> true for randomization tests. It might be a merely linguistic >>> discrimination, but it is important to note which assumptions have to be >>> (implicitly) made. >>> * I'm not sure what you mean by "mean differences" of the events - is that >>> two groups you are comparing? If so, that seems reasonable, but just make >>> sure the test statistic you use is reasonable and sensitive against the >>> alternatives you are mostly interested in. The randomization/permutation >>> test will never proof that, e.g., means are significantly different, but >>> only that there is SOME difference. By selecting the appropriate test >>> statistic, you can influence what will pop up more easily and what not, but >>> you can never be sure (unless you make strong assumptions about everything >>> else, like in many parametric tests). >>> * For any test statistic, you would then determine the proportion of its >>> values among the 5000 samples where it is as large or larger than the one >>> observed (or as small or smaller, or either, depending on the nature of the >>> test statistic and whether you aim for a one- or a two-sided test). That is >>> your p value. If small enough, conclude significance. At least conceptually >>> important: The observed test statistic is always part of the >>> re-randomization (i.e. your 5000) - so you truly only do 4999 plus the one >>> you observed. Otherwise the test may be more or less liberal. Your p value >>> is hence no smaller than 1/n, where n is the total number of samples you >>> looked at (including the observed one), a p value of 0 is not possible in >>> randomization tests (nor in other tests, of course). >>> >>> I hope this is helpful, but you will need to go through these and refer to >>> your own setup to check whether you adhered to the principles or not, which >>> is impossible for me to judge based on the information provided (and I >>> won't be able to look at excessive code to check either). >>> >>> Michael >>> >>>> -----Original Message----- >>>> From: R-help <r-help-boun...@r-project.org> On Behalf Of Ogbos Okike >>>> Sent: Montag, 28. Januar 2019 19:42 >>>> To: r-help <r-help@r-project.org> >>>> Subject: [R] Randomization Test >>>> >>>> Dear Contributors, >>>> >>>> I conducting epoch analysis. I tried to test the significance of my result >>>> using >>>> randomization test. >>>> >>>> Since I have 71 events, I randomly selected another 71 events, making sure >>>> that none of the dates in the random events corresponds with the ones in >>>> the real event. >>>> >>>> Following the code I found here >>>> (https://www.uvm.edu/~dhowell/StatPages/R/RandomizationTestsWithR/R >>>> andom2Sample/TwoIndependentSamplesR.html), >>>> I combined these two data set and used them to generate another 5000 >>>> events. I then plotted the graph of the mean differences for the 5000 >>>> randomly generated events. On the graph, I indicated the region of the >>>> mean difference between the real 71 epoch and the randomly selected 71 >>>> epoch. >>>> >>>> Since the two tail test shows that the mean difference falls at the >>>> extreme of >>>> the randomly selected events, I concluded that my result is statistically >>>> significant. >>>> >>>> >>>> >>>> I am attaching the graph to assistance you in you suggestions. >>>> >>>> I can attach both my code and the real and randomly generated events if you >>>> ask for it. >>>> >>>> My request is that you help me to understand if I am on the right track or >>>> no. >>>> This is the first time I am doing this and except the experts decide, I am >>>> not >>>> quite sure whether I am right or not. >>>> >>>> Many thanks for your kind concern. >>>> >>>> Best >>>> Ogbos >>>> ______________________________________________ >>>> 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. > > ______________________________________________ > 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. Ben Tupper Bigelow Laboratory for Ocean Sciences 60 Bigelow Drive, P.O. Box 380 East Boothbay, Maine 04544 http://www.bigelow.org Ecological Forecasting: https://eco.bigelow.org/ ______________________________________________ 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.
