This function will be called after an instance is built. User
input will be stored in the environment. The response variable of this model
is y. The formula of y is defined in SIMPLE_CUBIC_MODEL$formula, the null
formula is defined in SIMPLE_CUBIC_MODEL$null_formula, the alternative is
defined in SIMPLE_CUBIC_MODEL$alt_formula.
Arguments
- a
Numeric. Default is
a = 1.- b
Numeric. Default is
b = 1.- sigma
Positive numeric. Default is
sigma = 1.- x
Random variable or closed form expression. Default is
x = rand_uniform(-1, 1, env = new.env(parent = parent.env(self))).- e
Random variable or closed form expression. Default is
e = rand_normal(0, sigma, env = new.env(parent = parent.env(self))).
Examples
# Instantiate
x <- rand_uniform()
e <- rand_normal()
test <- simple_cubic_model(a = 200, b = 200, x = x, e = e)
test
#>
#> ── <SIMPLE_CUBIC_MODEL object>
#> y = 1 + x + a * x^2 + b * x^3 + e
#> - x: <RAND_UNIFORM object>
#> [a: 0, b: 1]
#> - e: <RAND_NORMAL object>
#> [mu: 0, sigma: 1]
#> Parameters:
#> - a: 200
#> - b: 200
#> - sigma: 1
# Generate data
test$gen(10)
#> y x e .resid .fitted
#> 1 168.53846 0.7030087 -1.4971662 -23.70854 192.246999
#> 2 303.31711 0.8922242 0.1585662 19.41738 283.899738
#> 3 159.53752 0.6851842 -0.3788172 -24.07557 183.613093
#> 4 166.67202 0.6975997 -0.2513820 -22.95495 189.626974
#> 5 75.89404 0.4976895 0.2023785 -16.89983 92.793873
#> 6 26.59478 0.3092583 0.2418459 25.07372 1.521064
#> 7 372.68988 0.9691593 0.8063879 51.52411 321.165770
#> 8 19.91782 0.2682683 0.3946286 38.25161 -18.333790
#> 9 140.99932 0.6501972 -0.1771570 -25.66668 166.666004
#> 10 84.94296 0.5247555 -0.5556692 -20.96124 105.904197
# Generate lineup
test$gen_lineup(10, k = 3)
#> y x e .resid .fitted test_name
#> 1 8.2979016 0.161186423 1.1029437 -0.1810592 8.478961 F-test
#> 2 256.4668756 0.832564333 0.5810179 46.9087077 209.558168 F-test
#> 3 84.6665356 0.523206639 -0.2507683 -32.2383011 116.904837 F-test
#> 4 4.2535880 0.099319639 0.9854447 14.3038692 -10.050281 F-test
#> 5 13.0242841 0.218025394 0.2264736 -12.4780776 25.502362 F-test
#> 6 1.4488015 0.005001875 0.4387708 39.7474671 -38.298666 F-test
#> 7 35.7144364 0.361099309 -1.1421487 -32.6388873 68.353324 F-test
#> 8 10.0986066 0.194766170 -0.1605784 -8.4375648 18.536171 F-test
#> 9 114.0838802 0.594807324 -0.3581386 -24.2655241 138.349404 F-test
#> 10 189.1403245 0.733409113 0.9306020 9.2793701 179.860954 F-test
#> 11 -8.0670428 0.161186423 1.1029437 -16.5460036 8.478961 F-test
#> 12 207.5567827 0.832564333 0.5810179 -2.0013852 209.558168 F-test
#> 13 104.0802194 0.523206639 -0.2507683 -12.8246173 116.904837 F-test
#> 14 -1.8858816 0.099319639 0.9854447 8.1643997 -10.050281 F-test
#> 15 0.2215766 0.218025394 0.2264736 -25.2807851 25.502362 F-test
#> 16 13.7648935 0.005001875 0.4387708 52.0635591 -38.298666 F-test
#> 17 42.2702022 0.361099309 -1.1421487 -26.0831215 68.353324 F-test
#> 18 5.8680439 0.194766170 -0.1605784 -12.6681274 18.536171 F-test
#> 19 127.0132471 0.594807324 -0.3581386 -11.3361571 138.349404 F-test
#> 20 226.3731930 0.733409113 0.9306020 46.5122386 179.860954 F-test
#> 21 -4.2545274 0.161186423 1.1029437 -12.7334883 8.478961 F-test
#> 22 205.0324757 0.832564333 0.5810179 -4.5256922 209.558168 F-test
#> 23 79.6824498 0.523206639 -0.2507683 -37.2223869 116.904837 F-test
#> 24 -32.5116747 0.099319639 0.9854447 -22.4613934 -10.050281 F-test
#> 25 77.6324531 0.218025394 0.2264736 52.1300913 25.502362 F-test
#> 26 -16.0025462 0.005001875 0.4387708 22.2961194 -38.298666 F-test
#> 27 50.8838919 0.361099309 -1.1421487 -17.4694318 68.353324 F-test
#> 28 -2.7992422 0.194766170 -0.1605784 -21.3354135 18.536171 F-test
#> 29 165.7153670 0.594807324 -0.3581386 27.3659627 138.349404 F-test
#> 30 193.8165869 0.733409113 0.9306020 13.9556325 179.860954 F-test
#> statistic p_value k null
#> 1 8174.6834385 4.937111e-11 1 FALSE
#> 2 8174.6834385 4.937111e-11 1 FALSE
#> 3 8174.6834385 4.937111e-11 1 FALSE
#> 4 8174.6834385 4.937111e-11 1 FALSE
#> 5 8174.6834385 4.937111e-11 1 FALSE
#> 6 8174.6834385 4.937111e-11 1 FALSE
#> 7 8174.6834385 4.937111e-11 1 FALSE
#> 8 8174.6834385 4.937111e-11 1 FALSE
#> 9 8174.6834385 4.937111e-11 1 FALSE
#> 10 8174.6834385 4.937111e-11 1 FALSE
#> 11 11.4741510 8.903986e-03 2 TRUE
#> 12 11.4741510 8.903986e-03 2 TRUE
#> 13 11.4741510 8.903986e-03 2 TRUE
#> 14 11.4741510 8.903986e-03 2 TRUE
#> 15 11.4741510 8.903986e-03 2 TRUE
#> 16 11.4741510 8.903986e-03 2 TRUE
#> 17 11.4741510 8.903986e-03 2 TRUE
#> 18 11.4741510 8.903986e-03 2 TRUE
#> 19 11.4741510 8.903986e-03 2 TRUE
#> 20 11.4741510 8.903986e-03 2 TRUE
#> 21 0.1754956 8.431973e-01 3 TRUE
#> 22 0.1754956 8.431973e-01 3 TRUE
#> 23 0.1754956 8.431973e-01 3 TRUE
#> 24 0.1754956 8.431973e-01 3 TRUE
#> 25 0.1754956 8.431973e-01 3 TRUE
#> 26 0.1754956 8.431973e-01 3 TRUE
#> 27 0.1754956 8.431973e-01 3 TRUE
#> 28 0.1754956 8.431973e-01 3 TRUE
#> 29 0.1754956 8.431973e-01 3 TRUE
#> 30 0.1754956 8.431973e-01 3 TRUE
# Plot the lineup
test$plot_lineup(test$gen_lineup(100))
