Splits x into n_segments non-overlapping equal segments,
periodograms each, and averages the result. Variance scales as
1 / n_segments at the cost of frequency resolution.
Examples
set.seed(1)
fs <- 1024L
t <- seq(0, (fs - 1) / fs, length.out = fs)
x <- sin(2 * pi * 50 * t) + 0.1 * rnorm(fs)
morie_dsp_psd_bartlett(x, fs = fs, n_segments = 4L)
#> $freqs
#> [1] 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68
#> [19] 72 76 80 84 88 92 96 100 104 108 112 116 120 124 128 132 136 140
#> [37] 144 148 152 156 160 164 168 172 176 180 184 188 192 196 200 204 208 212
#> [55] 216 220 224 228 232 236 240 244 248 252 256 260 264 268 272 276 280 284
#> [73] 288 292 296 300 304 308 312 316 320 324 328 332 336 340 344 348 352 356
#> [91] 360 364 368 372 376 380 384 388 392 396 400 404 408 412 416 420 424 428
#> [109] 432 436 440 444 448 452 456 460 464 468 472 476 480 484 488 492 496 500
#> [127] 504 508 512
#>
#> $psd
#> [1] 1.552266e-04 4.252729e-04 2.971231e-04 4.779557e-04 4.653324e-04
#> [6] 5.164753e-04 5.553273e-04 5.878052e-04 9.554746e-04 1.656424e-03
#> [11] 2.444684e-03 6.085435e-03 5.350193e-02 4.910284e-02 4.908806e-03
#> [16] 1.619802e-03 7.814509e-04 4.632055e-04 2.318642e-04 2.242210e-04
#> [21] 1.783453e-04 1.117405e-04 1.069812e-04 7.075959e-05 6.420485e-05
#> [26] 3.421504e-05 1.429858e-05 5.476485e-05 5.172870e-05 3.280501e-05
#> [31] 6.345749e-05 2.704543e-05 2.528544e-05 3.519217e-05 4.807614e-05
#> [36] 2.668768e-05 4.978886e-05 1.659609e-05 3.344483e-05 1.397066e-05
#> [41] 3.682868e-05 9.466937e-06 9.146976e-06 1.750176e-05 3.291501e-05
#> [46] 1.272009e-05 1.526187e-05 2.940441e-05 1.219743e-05 2.902606e-05
#> [51] 2.185057e-05 2.937746e-05 3.692435e-05 3.747312e-05 2.401720e-05
#> [56] 1.538451e-05 3.871615e-05 1.192979e-05 4.570365e-05 4.153971e-05
#> [61] 1.161143e-05 7.765237e-06 2.102811e-05 2.064671e-05 3.038406e-05
#> [66] 2.241154e-05 2.910688e-05 2.894868e-05 2.194463e-05 2.495359e-05
#> [71] 2.046153e-05 2.535140e-05 1.658584e-05 1.019672e-05 1.916205e-05
#> [76] 3.893672e-05 1.337247e-05 1.699991e-05 2.124965e-05 1.898157e-05
#> [81] 1.606300e-05 3.070018e-05 8.605538e-06 3.350302e-05 1.177876e-05
#> [86] 1.592686e-05 1.328106e-05 1.482400e-05 1.040061e-05 2.534662e-05
#> [91] 2.877685e-05 1.673989e-05 1.149070e-05 1.745111e-05 2.547587e-05
#> [96] 1.526660e-05 5.954893e-06 4.669321e-05 1.075729e-05 8.719574e-06
#> [101] 8.036827e-05 1.643231e-05 7.893331e-06 5.394363e-05 2.183228e-05
#> [106] 2.104430e-05 1.066430e-05 3.960400e-05 3.094256e-05 1.642682e-05
#> [111] 4.325197e-05 7.119722e-06 1.660421e-05 2.776885e-05 1.972386e-05
#> [116] 1.615422e-05 3.028253e-05 2.290978e-05 2.721803e-05 2.175734e-05
#> [121] 5.007471e-05 3.775198e-05 7.909204e-06 2.211875e-05 1.150676e-05
#> [126] 8.551010e-06 8.885068e-06 1.092487e-05 2.402295e-06
#>