Sentences with phrase «fitting a curve through»

Fitting a curve through 10 years of data isn't a very good idea — if you use the full set you obviously get a very different answer.

Not exact matches

The great thing about these yoga pants is that they fit like a pair of leggings through the hips and thighs, hugging your curves while providing lots of support and stretch.

The softly textured skirt drapes beautifully over your curves, allowing plenty of room to grow, while a discreet stretch panel at the back ensures a flexible fit through every stage of pregnancy.

Finely knit in the softest cotton modal, it drapes beautifully over your curves, providing a flexible fit through every stage of pregnancy.

Designed from super-soft cotton - blend brushback fleece, this dress has a funnel neck that can be worn unrolled, a curved hem that's slightly higher at the front and A-line shaping through the body for a relaxed fit.

So we grab a coffee while a new set of pads is fitted, along with a pair of the optional 20in rims for the front to see if they give less understeer through the Palmer Curves.

Using front struts and a rear twist beam the setup manages to deliver a comfortable ride and agile handling — through my favourite set of sweeping curves the Fit displayed minimal body roll and understeer only surfaced when liberties were taken.

Return0 = y and HSWR50 = x. Years R - Squared Equation 1... 0.0908 y = 2.647 x - 10.053 2... 0.1704 y = 2.6542 x - 10.527 3... 0.2519 y = 2.506 x - 9.8705 4... 0.3386 y = 2.5412 x - 10.112 5... 0.4022 y = 2.4671 x - 9.7509 6... 0.4710 y = 2.6452 x - 9.7732 7... 0.5370 y = 2.4858 x - 9.8994 8... 0.6018 y = 2.4853 x - 9.9486 9... 0.6775 y = 2.4061 x - 9.5746 10... 0.7381 y = 2.341 x - 9.2439 11... 0.8002 y = 2.3113 x - 9.107 12... 0.8643 y = 2.33 x - 9.2065 13... 0.8949 y = 2.2709 x - 8.8728 14... 0.9027 y = 2.1245 x - 8.0652 15... 0.8964 y = 1.9819 x - 7.2668 16... 0.8773 y = 1.8006 x -6.2552 17... 0.8665 y = 1.6398 x - 5.3589 18... 0.8509 y = 1.5422 x - 4.7903 19... 0.8036 y = 1.412 x - 4.0325 20... 0.7286 y = 1.2552 x - 3.1208 21... 0.6626 y = 1.1094 x - 2.2726 22... 0.6045 y = 0.9825 x - 1.5285 23... 0.5293 y = 0.8381 x - 0.6976 24... 0.4287 y = 0.6779 x + 0.2077 25... 0.3156 y = 0.5041 x + 1.1781 26... 0.2079 y = 0.3336 x + 2.1127 27... 0.1100 y = 0.2031 x + 2.829 28... 0.0380 y = 0.1084 x + 3.3421 29... 0.0109 y = 0.0603 x + 3.583 30... 0.0004 y = 0.0116 x + 3.8169 Return0 = y and HSWR80 = x. Years R - Squared Equation 1... 0.1258 y = 2.9412 x - 12.533 2... 0.2332 y = 2.9192 x - 13.189 3... 0.3294 y = 2.6717 x - 11.883 4... 0.4193 y = 2.616 x - 11.611 5... 0.4715 y = 2.4141 x - 10.377 6... 0.5241 y = 2.2778 x - 9.5372 7... 0.5778 y = 2.2064 x - 9.0847 8... 0.6309 y = 2.1431 x - 8.7466 9... 0.6951 y = 2.0267 x - 8.0839 10... 0.7478 y = 1.9526 x - 7.6448 11... 0.8085 y = 1.9398 x - 7.5947 12... 0.8703 y = 1.9776 x - 7.8088 13... 0.9001 y = 1.9485 x - 7.584 14... 0.9045 y = 1.8432 x - 6.8875 15... 0.8910 y = 1.7278 x - 6.112 16... 0.8566 y = 1.5774 x - 5.1143 17... 0.8395 y = 1.4588 x - 4.3331 18... 0.8151 y = 1.3856 x - 3.8072 19... 0.7602 y = 1.2813 x - 3.0685 20... 0.6819 y = 1.1517 x - 2.1588 21... 0.6170 y = 1.0346 x - 1.3363 22... 0.5699 y = 0.9358 x - 0.6359 23... 0.5099 y = 0.8232 x + 0.1334 24... 0.4265 y = 0.6936 x + 0.9921 25... 0.3218 y = 0.5417 x + 1.9799 26... 0.2284 y = 0.4031 x + 2.852 27... 0.1451 y = 0.2931 x + 3.542 28... 0.0826 y = 0.2118 x + 4.0356 29... 0.0551 y = 0.1774 x + 4.2041 30... 0.0318 y = 0.1399 x + 4.3784 Notice that the curve fit is especially good from years 11 through 19 for HSWR50 (with 50 % stocks) and 11 through 18 for HSWR80 (with 80 % stocks).

Test of the Hasselmann model through a regression analysis, where the coloured curves are the best - fit modelled values for Q based on the Hasselmann model and global mean temperatures (PDF).

The linear effects that ENSO and volcanic aerosols have on global temperatures are well documented through a multitude of different analyses, including «curve - fitting».

Fitting any type continuous curve through long term temperature does not reflect the earth's climate variations, thus is not an acceptable mathematical modeling technique.

(Actually he's only using 11 coefficients because if you scale Amp1 by x and divide Scale1 through Scale5 by x you get back the same curve with the same fit, i.e. the coefficients are not linearly independent.

As we imagine increasingly curvy lines, what stops us from fitting a curve that goes right through the center of each of our data points?

Design consisted of multiple stages including multiplication, summing and division that acquired 4 sets of raw LADAR input data and pipelined each section through the curve fit process.