📄 q22.m
字号:
function data1
Y=data;
P=[4.2 4 12.48 68.3 1.41 2.451 2.552 85.9 97.8
4.1 4 12.08 67 1.36 2.445 2.549 85.3 97.5
4.1 4 12.42 67.55 4.2 2.45 2.553 84 97.6
4 5.1 13.03 60.66 0 2.425 2.556 0 0
8.6 5.45 21.84 75.03 0 2.358 2.494 0 0
4.5 4.23 13.05 67.61 1.18 2.421 2.535 0 0
5 4.27 14.68 70.89 1.5 2.53 2.646 0 0
4.1 4.15 12.47 66.72 1.51 2.449 2.555 83.9 97.7
4.2 4 12.12 67 1.42 2.447 2.55 86.4 97.9
4.5 4.42 13.71 67.82 0 2.422 2.534 0 0
4.1 4.1 12.31 66.7 1.4 2.441 2.546 86 97.2
4.1 4 14.18 71.79 1.17 2.494 2.596 86 97.9
4.1 4 12.24 66.5 1.54 2.465 2.57 85.2 97.1
4.5 4 13.08 69.43 1.23 2.447 2.549 84.8 97.5
5 4.35 14.29 69.76 1.34 2.44 2.551 0 0
4.1 4.1 12.24 66.4 1.54 2.454 2.558 85.2 97.4
4.4 4.1 13.1 68.7 1.42 2.437 2.538 85.5 97.6
5 5.04 14.52 69 1.4 2.393 2.52 0 0
4.1 4 12.31 67.51 1.42 2.482 2.588 86 97.6
4.5 4.1 13.4 69.41 1.21 2.464 2.564 84.6 97.4
4.1 4 12.34 67.59 1.45 2.455 2.558 86.4 97.7
4.5 4 13.1 69.47 1.15 2.442 2.543 85.4 97.4
4.8 4.4 13.67 0 0 2.413 2.524 0 0
4.1 4 12.18 67.17 1.41 2.475 2.578 84.3 97.1
4.4 4.2 13.28 68.53 1.32 2.456 2.559 85.4 97.5
4.5 4.35 13.48 67.74 0 0 2.528 0 0
4.1 3.9 12.77 69.46 1.44 2.539 2.648 86 97.7
4.3 4.1 13.27 69.09 1.45 2.534 2.643 85.4 97.1
4.9 4.05 14.07 71.22 1.5 2.489 2.594 0 0
4 4 12.51 68.03 1.35 2.55 2.656 84.7 97.5
4 4 12.51 68.03 1.32 2.554 2.655 85 97.7
4.4 4.1 12.4 67.01 1.51 2.436 2.541 84 97.2
4.6 4.2 13.07 68.24 1.22 2.436 2.541 83.5 97.1
5 4.58 15 69.5 1.49 2.417 2.533 0 0
4.1 3.8 12.77 69.46 1.44 2.547 2.65 86 97.7
4.6 3.9 13.63 71.4 1.06 2.468 2.569 83.6 97.6
4.9 4.1 15.08 72.82 1.14 2.462 2.564 85.4 97.4
4.7 4.1 13.19 69.06 1.45 2.422 2.525 84.8 97.8
5.2 4.1 14.68 71.99 1.5 2.482 2.588 84.6 97
4.7 4.21 14.03 69.97 0 2.409 2.515 0 0
5.7 4.3 16.5 73.8 0 2.55 2.665 0 0
4.5 4.2 13.19 68.46 1.25 2.415 2.513 83.1 97.3
4.5 4.1 13.21 68.73 1.23 2.499 2.604 85.2 97.2
4.9 4.27 14.51 70.54 1.4 2.464 2.574 0 0
4.6 4 13.31 69.96 1.23 2.428 2.531 85.4 97.7
4.2 4 12.5 68 0 2.434 2.536 0 0
4.1 3.8 12.14 68.35 1.23 2.453 2.55 0 0
4.5 4.1 13.45 69.44 1.27 2.427 2.531 84.4 97
4.5 4 13.11 69.19 1.32 2.431 2.534 85.7 97.3
4.5 4.1 13.03 68.54 1.33 2.426 2.533 85 97.4
4.6 4.2 13.9 69.8 0 2.415 2.52 0 0
4.6 4.1 13.17 68.78 1.28 2.435 2.539 85.1 97.2
4.5 4.8 14.01 65.92 0 2.41 2.531 0 0
6.1 4.1 16.6 75.6 0 2.483 2.59 0 0
4.1 3.7 11.8 68.8 0 2.438 2.531 0 0
4.1 3.9 12.1 67.1 0 2.436 2.534 0 0
4.5 4.43 13.63 67.5 0 2.42 2.532 0 0
4 3.9 12.11 67.79 1.3 2.507 2.61 85.2 97.3
4.4 4.1 13.13 68.78 1.27 2.477 2.583 85.6 97.5
4.5 4.1 13.04 68.8 1.11 2.426 2.53 84.9 97.7
4 4.12 12.2 66.2 0 2.441 2.546 0 0
4.4 4.05 13.36 69.7 0 2.418 2.52 0 0
4.6 3.9 13.34 70.76 1.24 2.423 2.523 86.2 97.6
4.6 4 13.59 71.3 1.23 2.433 2.535 85.7 97.5
5.2 4 14.76 72.64 1.53 2.472 2.576 85.9 98
4.4 4.1 13.47 69.57 1.28 2.466 2.57 85.7 97.5
4 4.5 12.54 71.29 1.4 2.489 2.581 85.5 98.3
4.2 4 12.28 67.36 0 2.492 2.596 0 0
4 4.3 12.6 65.8 0 2.442 2.552 0 0
6.1 4.13 16.7 75.2 0 2.481 2.586 0 0
4.5 3.9 12.8 69.6 0 2.42 2.518 0 0
4.5 4.1 13.2 69.2 0 2.414 2.516 0 0
4.5 4 12.8 69.1 0 2.42 2.52 0 0
4.3 4.1 12.71 67.75 0.89 2.408 2.51 86.7 97.2
4.2 4 12.25 67.36 1.56 2.41 2.511 85.2 97.8
4.4 4.1 12.58 67.4 1.58 2.438 2.543 85.2 97.6
4.4 3.9 12.93 69.52 1.37 2.442 2.545 86.1 97.3
4.8 4.2 14.03 72.77 1.29 2.521 2.63 86.1 97.1
4.5 4.12 13.2 68.8 1.36 2.403 2.506 85.1 97.3
4.7 4.29 13.87 69.1 0 2.408 2.516 0 0
6.1 3.9 16.5 76.7 0 2.49 2.59 0 0
6.1 4.05 16.58 75.6 0 2.486 2.591 0 0
6.1 4 16.6 75.9 0 2.486 2.59 0 0
4.8 4 13.7 70.8 1.28 2.422 2.524 85.3 97.7
4.5 4.1 13.1 68.71 1.27 2.429 2.533 84.4 97.5
4.5 4 13.04 69.3 1.27 2.43 2.532 84.6 97.1
3.7 5.13 13.04 60.8 0 2.443 2.575 0 0
6 4.1 16.7 75.4 0 2.54 2.649 0 0
6 4.07 16.6 75.4 0 2.496 2.602 0 0
5.1 3.9 14.27 72.67 1.07 2.372 2.474 85.4 97.6
5 4.1 14.61 71.66 1.29 2.385 2.496 85 97.2
4.5 4.2 13.3 68.17 1.32 2.416 2.523 0 0
4.6 4.3 14 69.3 0 2.408 2.517 0 0
4.6 4.1 13.47 69.84 1.14 2.431 2.535 86.1 96.9
4.6 4.3 13.47 68.19 0 2.412 2.52 0 0
4.5 4 13.21 69.73 1.31 2.432 2.533 85.3 97.4
8.6 5.43 22.6 75.99 0 2.441 2.581 0 0
5 4.17 14.4 71 1.491 2.436 2.542 0 0
4.5 4.58 13.45 65.9 1.08 2.419 2.535 0 0
4.5 4.33 12.7 65.88 1.44 2.385 2.493 0 0
6.1 4.36 17.07 74.46 0 2.527 2.635 0 0
5.2 4.15 14.1 70.57 1.28 2.402 2.504 85.2 97.1
6.1 4.06 16.97 76.1 0 2.485 2.59 0 0
6 4.05 16.93 76.1 0 2.532 2.639 0 0
4.3 4.2 13.43 68.73 1.32 2.563 2.671 86.2 97
6.2 4.1 16.5 75 0 2.473 2.58 0 0
6.1 4 17 76.4 0 2.538 2.644 0 0
6.1 3.9 16.64 76.49 0 2.481 2.582 0 0
6.1 4.1 16.8 75.8 0 2.52 2.627 0 0
3.9 3.9 12.07 67.28 1.44 2.461 2.561 85.7 97.8
4.6 4.45 13.55 67.2 0 2.386 2.497 0 0
6.1 4.08 16.84 75.74 0 2.513 2.62 0 0
6.2 4.1 16.6 75.3 0 2.488 2.595 0 0
4.4 4 13.14 69.57 1.35 2.488 2.613 85.1 97.3
5 4.15 14.33 70.05 1.46 2.485 2.594 0 0
6.1 4.1 16.6 75.4 0 2.485 2.591 0 0
6.1 3.99 17.15 76.71 0 2.5 2.604 0 0
5.1 4.23 14.49 70.77 1.49 2.488 2.598 0 0
6.2 3.8 16.5 77 0 2.481 2.584 0 0
6 4.1 16.6 75.3 0 2.508 2.616 0 0
5.3 4 14.14 71.5 1.25 2.427 2.53 86.1 97.7
4.5 4.2 13.71 69.59 1.1 2.522 2.635 84.9 96.9
5.2 4.35 15.32 71.2 0 2.573 2.69 0 0
6.2 4.19 16.79 75.04 0 2.469 2.577 0 0
5.1 4.18 14.06 70.28 1.58 2.407 2.512 0 0
4.3 3.9 12.7 69.6 1.19 2.594 2.702 86.9 97.8
6.1 3.99 17.1 76.8 0 2.526 2.631 0 0
6.1 3.98 16.9 76.4 0 2.511 2.615 0 0
6.1 3.87 16.5 76.6 0 2.485 2.585 0 0
6.1 3.8 16.8 77.4 0 2.534 2.634 0 0
6 3.95 17 76.7 0 2.552 2.657 0 0
4.6 4.2 13.58 69.04 0 2.415 2.521 0 0
6 3.72 16.6 77.6 0 2.514 2.611 0 0
6.2 4.1 16.51 75.18 0 2.505 2.612 0 0
6.1 3.96 16.63 76.22 0 2.471 2.598 0 0
6 4.1 16.55 75.03 0 2.53 2.638 0 0
5.1 4.15 14.33 71.05 0 2.472 2.579 0 0
3.7 5.27 13 59.46 0 2.447 2.582 0 0
5.2 3.93 14.98 73.76 1.12 2.43 2.568 86.4 97.7
6.2 4.19 16.79 75.04 0 2.465 2.574 0 0
5.1 4.36 14.71 70.37 1.48 2.415 2.525 0 0
4.4 4.46 13.89 67.9 1.33 2.443 2.557 0 0
4 4.07 12.2 66.7 1.34 2.448 2.553 85.4 97.5
6.1 4.12 16.5 75.1 0 2.504 2.611 0 0
4.7 0 0 0 0 0 0 0 0
4.6 3.88 13.3 70.7 1.3 2.436 2.54 84.2 97.3
4.5 4.02 13.3 69.8 1.49 2.482 2.585 85.1 97.8
4.5 4.02 13.3 69.8 1.49 2.482 2.585 85.1 97.8
4.4 4.15 13.1 68.4 1.49 2.483 2.59 85.5 97.3
4.4 4.2 13.3 68.1 1.5 2.45 2.558 85.4 97.4
6.1 4.16 17.3 76 0 2.488 2.596 0 0
6 4.2 17.3 75.7 0 2.533 2.644 0 0
6 4.07 17.1 76.2 0 2.522 2.629 0 0
6 4.03 17 76.3 0 2.523 2.629 0 0
3.8 4.8 12.9 62.6 1.13 2.536 2.664 0 0
6 3.9 16.9 76.8 0 2.505 2.607 0 0
4.7 4.6 13.5 65.9 1.59 2.404 2.52 0 0
4.9 4.3 14.9 71 1.43 2.409 2.518 0 0
5.1 4.3 14.6 70.8 1.28 2.443 2.552 0 0
3.6 4.85 12.4 60.9 1.4 2.45 2.575 0 0
4.4 4.7 14 66.7 1.4 2.422 2.54 0 0
5.1 4.6 14.6 68.3 1.64 2.546 2.67 0 0
3.8 5.83 13.39 56.47 0 2.406 2.555 0 0
4.1 3.98 12.2 67.8 1.07 2.446 2.545 81.6 97.3
4.1 4.3 12 64.08 1.43 2.44 2.55 0 0
0 5.46 21.5 74.6 0.24 2.267 2.397 0 0
4.1 4.06 12.13 66.16 1.33 2.363 2.536 85.4 97.5
4 4.2 12.37 66.4 1.2 2.441 2.543 84.6 97.6
3.7 5.46 12.85 57.6 0 2.415 2.559 0 0
4.1 4.3 12.71 66.1 1.19 2.437 2.547 84.9 96.6
4.4 4 13.13 69.15 1.22 2.447 2.55 84.4 97.7
5.2 4.45 14.3 68.8 1.4 2.446 2.56 0 0
5.1 4.46 14 68.6 1.6 2.443 2.557 0 0
5.1 4.46 14 68.6 1.6 2.443 2.557 0 0
4.6 3.86 13.5 71.39 1.3 2.44 2.538 85.9 97
4.8 4.37 13.9 68.6 1.35 2.45 2.562 0 0
4.8 4 14.4 72 1.18 2.444 2.65 85.5 97.8
5 0 0 0 0 2.509 2.633 0 0
4.7 4 13.07 69.4 1.38 2.547 2.653 86.8 97.1
4.4 3.9 13.5 71.4 1.3 2.448 2.555 85.9 97
5.4 4.15 15 72.4 1.46 2.428 2.533 86.1 97.7
5.5 4 15.41 74.04 1.36 2.45 2.553 86.3 97.8
5.3 4.1 14.8 72.3 1.55 2.516 2.612 85.2 97.7
4.6 6.23 0 0 0 2.337 2.492 0 0
4.9 0 0 0 0 2.463 2.681 0 0
4.8 4.08 13.7 70.2 1.55 2.542 2.65 0 0
6.1 0 0 0 0 2.491 2.596 0 0
7 4.5 18.14 74.91 0 2.351 2.461 0 0
4.6 4.43 13.64 67.54 1.6 2.417 2.529 0 0
5.1 4.3 14.6 70.8 1.28 2.443 2.552 0 0
6 4.11 16.94 75.8 0 2.53 2.638 0 0
5.6 4 15.33 73.91 1.39 2.537 2.651 87.8 97
4.1 4.69 13.02 63.98 1.48 2.458 2.579 85.4 97.8
3.9 4.08 13.15 69 1.39 2.558 2.673 85.5 97.4
4.1 4 13.23 69.38 1.19 2.55 2.66 85.6 97.3
3.9 4.08 13.08 68.81 1.57 2.526 2.647 85 97.3
4.4 3.94 13.25 70.26 1.3 2.532 2.645 85.1 97.5
3.9 4.1 12.01 65.86 1.58 2.502 2.609 85.6 97.3
3.6 4.03 12.39 67.5 1.24 2.558 2.685 84.8 97.09
4.1 4 12.35 67.61 1.38 2.478 2.591 84 97.7
4.1 4 12.31 67.49 1.45 2.498 2.603 83.7 97.5
4.1 4.79 12.95 62.9 1.38 2.517 2.644 0 0
3.9 4 12.51 68.03 1.47 2.47 2.586 83.5 97.7
4 4.39 12.4 64.58 1.52 2.503 2.618 86.2 98
6.1 4.04 16.94 76.2 0 2.514 2.622 0 0
5.5 3.96 14.91 73.44 1.39 2.458 2.568 85.7 97.6
4.8 4.19 14.61 71.31 1.21 2.4 2.505 0 0
4.8 4.02 14.31 71.92 1.17 2.507 2.612 0 0
4.8 3.97 14.24 71.12 1.29 2.394 2.493 0 0
4.1 4.08 12.29 66.78 1.46 2.444 2.548 0 0
4.6 4.15 13.31 68.8 1.33 2.424 2.529 0 0
4.2 4.01 12.63 68.26 1.37 2.443 2.545 0 0
4.1 4 12.48 68.3 1.41 2.451 2.552 85.9 97.8
4 4 13.74 70.88 0 0 0 84.4 97.7
4.7 4.08 14.21 71.28 1.56 2.491 2.598 87 97.7
4.1 4.3 12.37 65.23 1.42 2.449 2.556 85.7 97.1
4.8 4.19 14.57 71.23 1.12 2.399 2.504 0 0
4.7 4.03 13.63 70.45 1.36 2.43 2.532 0 0
4.5 4.1 13.05 68.36 1.47 2.461 2.567 84.9 97.7
4.2 4.2 12.34 65.97 1.32 2.462 2.569 85 97.1
5 4.73 14.74 67.93 1.29 2.52 2.645 0 0
4.2 4.08 13.09 68.84 1.23 2.438 2.534 84.9 97.8
4.2 4.1 12.19 66.36 1.41 2.44 2.539 84.5 97.4
4.2 3.99 13.08 69.51 1.25 2.432 2.536 85.4 97.6
5.2 3.96 15.22 73.97 1.4 2.46 2.56 85.6 97.5
6 4.08 16.6 75.4 0 2.537 2.645 0 0
4.1 4.12 13.08 68.5 1.1 2.423 2.527 85 97.3
4.2 4.08 12.23 66.65 1.14 2.434 2.538 85.6 97.1
4.1 4.05 12.15 66.67 1.38 2.438 2.545 84.9 97.6
4.2 4.1 13.03 68.52 1.12 2.427 2.53 84.9 97
6 3.74 16.65 77.52 0 2.546 2.645 0 0
4.1 4.1 13.31 69.56 1.37 2.537 2.659 83.5 97.5
4.9 4.52 15.07 69.96 1.18 2.56 2.681 0 0
4.8 4.31 14.77 70.83 1.15 2.531 2.645 0 0
4.9 4.36 14.87 70.7 1.2 2.546 2.662 0 0
6 4.09 16.84 75.73 0 2.558 2.667 0 0
3.7 4 12.1 66.6 1.47 0 2.646 86.3 97.2
3.8 4.1 12.1 66 1.41 2.451 2.56 84.9 97.5
4.9 4.63 14.49 68.04 1.6 2.532 2.655 0 0
6.2 4.11 16.62 75.29 0 2.522 2.63 0 0
4 4.69 13.27 64.69 1.6 2.44 2.56 0 0
4.7 4.37 14.28 69.37 1.07 2.558 2.675 0 0
4.9 4.2 14.64 71.33 1.18 2.534 2.645 0 0
4.1 4.01 13.06 69.3 1.36 2.487 2.59 84 97.3
4.6 4.98 14.61 65.9 1.26 2.499 2.63 0 0
4 4 13.15 69.88 1.15 2.52 2.626 85.1 97.1
4.2 4.25 12.86 66.96 1.54 2.451 2.552 85.9 97.8
4 4.03 12.66 68.13 1.673 2.712 2.826 0 0
8.4 5.62 21.93 74.35 0 2.433 2.578 0 0
6 4.08 17.22 76.31 0 2.539 2.647 0 0
4 4 13.13 69.46 1.1 2.443 2.578 84.9 97.3
4.5 4.3 13.42 68.1 1.35 2.425 2.534 0 0
6.1 4.23 17.06 75.22 0 2.492 2.601 0 0
4.5 4.29 13.4 67.95 1.39 2.43 2.539 0 0
4.4 4.6 13.66 66.36 1.53 2.408 2.524 0 0
4.9 3.87 14.89 74.01 0.94 0 0 86.5 97.7
4.4 4.55 13.58 66.49 1.36 2.433 2.549 0 0
5.2 4.5 14.53 69 8.12 2.481 2.598 0 0
4.2 4.08 13.36 69.47 1.24 2.521 2.625 86.3 97.7
4.2 4.08 13.13 68.94 0.99 2.45 2.548 84.7 97.8
5.1 4.21 14.4 70.75 1.28 2.411 2.517 0 0
4.2 4.13 13.01 68.26 1.13 2.432 2.541 84 97.1
4.2 4 13.07 69.32 1.15 2.439 2.543 83.2 97.2
4.6 4 13.42 70.27 1.23 2.433 2.835 86.3 97.4
5.1 4.49 14.53 69.08 1.48 2.488 2.605 0 0
5.1 4.53 14.6 68.95 1.48 2.486 2.604 0 0
6 3.98 16.74 76.24 0 2.566 2.664 0 0
4.8 3.98 14.06 71.7 0.97 2.414 2.514 85.3 97.2
6.2 4.1 16.5 75.3 0 2.371 2.472 0 0
5.5 4.1 13.67 70.04 1.53 2.342 2.442 0 0
3.8 4.01 12.03 66.68 1.27 2.451 2.549 86.4 96
5 4.64 15.15 69.36 1.43 2.485 2.605 0 0
4.9 4.61 15.22 69.73 1.09 2.487 2.605 0 0
4.9 4.07 14.74 72.38 1.2 2.381 2.484 86.5 95.9
4.8 4.04 14.02 71.19 1.03 2.378 2.476 86.3 97.8
5 4.36 14.37 69.69 1.15 2.525 2.64 0 0
4.3 4.45 13.09 66.02 1.45 2.384 2.495 0 0
4.6 4 13.48 70.4 1.23 2.427 2.532 84.2 97.3
5.1 4.21 14.32 70.61 1.37 2.481 2.59 0 0
4.8 4.92 13.18 62.7 1.7 2.437 2.563 0 0
4.3 4.04 13.06 69.07 1.51 2.433 2.537 85.8 97.9
4.5 4.5 13.55 66.8 1.18 2.442 2.557 0 0
3.9 4.06 12.26 66.88 1.41 2.488 2.586 86.4 95.9
6.2 3.88 16.52 76.5 0 2.501 2.602 0 0
6.2 4.16 16.73 75.11 0 2.463 2.57 0 0
4.6 4.18 13.2 68.35 1.15 2.387 2.491 0 0
4.6 4.21 13.23 68.17 1.07 2.388 2.493 0 0
6.2 4.15 16.77 75.28 0 2.474 2.581 0 0
4.3 4 13.1 69.7 1.3 2.443 2.544 83.9 97.1
6.11 0 0 0 0 0 2.653 0 0
];
Plen=length(P);
Pvalue=0;
Pvalue1=0;
Pvalue2=0;
Pvalue3=0;
Pvalue4=0;
for i=1:Plen
mark = 0;
for j=1:9
if(P(i,j)==0)
mark=1;
end
end
if(mark==0)%全部是非0数据
Pvalue=Pvalue+1;
PP(Pvalue,:)=P(i,:);
%%加上常数项
if(Y(i,1))
Pvalue1=Pvalue1+1;
P1(Pvalue1,:)=[P(i,:) 1 Y(i,1)];
end
if(Y(i,2))
Pvalue2=Pvalue2+1;
P2(Pvalue2,:)=[P(i,:) 1 Y(i,2)];
end
if(Y(i,3))
Pvalue3=Pvalue3+1;
P3(Pvalue3,:)=[P(i,:) 1 Y(i,3)];
end
if(Y(i,4))
Pvalue4=Pvalue4+1;
P4(Pvalue4,:)=[P(i,:) 1 Y(i,4)];
end
end
end
%处理得出各个指标和相关参数的非零关系P1，P2，P3，P4
%b = regress(P1(:,10),P1(:,1:9));
%[b,bint,r,rint,stats] = regress(P1(:,10),P1(:,1:9));
[PC,score,latent,tsquare]=princomp(PP);
%PP(1,:)=PP(1,:)*1000;
%covx = cov(PP);
%[PC1,score1,latent1,tsquare1]=princomp(PP);
%[COEFF, LATENT] = PCACOV(PP);
clc
%计算主分量与四个标准的关系
%Pvalue=0;
Pvalue1=0;
Pvalue2=0;
Pvalue3=0;
Pvalue4=0;
PC_2=PC(:,1:2);
PPP=PP*PC_2;%两个主分量
Plen=length(PPP);
for i=1:Plen
if(Y(i,1))
Pvalue1=Pvalue1+1;
P_1(Pvalue1,:)=[PPP(i,:) 1 Y(i,1)];
end
if(Y(i,2))
Pvalue2=Pvalue2+1;
P_2(Pvalue2,:)=[PPP(i,:) 1 Y(i,2)];
end
if(Y(i,3))
Pvalue3=Pvalue3+1;
P_3(Pvalue3,:)=[PPP(i,:) 1 Y(i,3)];
end
if(Y(i,4))
Pvalue4=Pvalue4+1;
P_4(Pvalue4,:)=[PPP(i,:) 1 Y(i,4)];
end
end
[b1,bint1,r1,rint1,stats1] = regress(P_1(:,4),P_1(:,1:3));
stepwise(P_1(:,1:3),P_1(:,4));
rcoplot(r1,rint1);
[b2,bint2,r2,rint2,stats2] = regress(P_2(:,4),P_2(:,1:3));
stepwise(P_2(:,1:3),P_2(:,4));
rcoplot(r2,rint2);
[b3,bint3,r3,rint3,stats3] = regress(P_3(:,4),P_3(:,1:3));
stepwise(P_3(:,1:3),P_3(:,4));
rcoplot(r3,rint3);
[b4,bint4,r4,rint4,stats4] = regress(P_4(:,4),P_4(:,1:3));
stepwise(P_4(:,1:3),P_4(:,4));
rcoplot(r4,rint4);
clc;
%Pcov=cov(PP)
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