 Probability Tutorials 121-140
 Theorems A | B | C | D | E | F | G | H | I | J | L | M | N | O | P | R | S | T | U | V | W
Contents
 Theorem 121: Jacobian formula 1 (non-negative case) Theorem 122: Jacobian formula 2 (L1 case) Theorem 123: Reduced normal (gaussian) density Theorem 124: Fourier tramsform of reduced normal distribution Theorem 125: Absolute continuity of convolution Theorem 126: Uniqueness of narrow limit of complex measures Theorem 127: Narrow continuity of convolution Theorem 128: Injectivity of fourier transform Theorem 129: Characterictic function determines distribution Theorem 130: Moments of measure from fourier transform Theorem 131: Diagonalisation of symmetric non-negative matrix Theorem 132: Fourier transform of gaussian measure Theorem 133: Gaussian measure has moments of all order Theorem 134: Mean and covariance of gaussian measure Theorem 135: Characteristic function of gaussian vector Theorem 136: Mean and covariance of gaussian vector Theorem 137: Characteristic function of normal random variable Theorem 138: Linear transformation of gaussian vector is gaussian Theorem 139: Gaussian vector criterion in terms of coordinates Theorem 140: Density of gaussian measure
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Theorems   1-20
Theorems 21-40
Theorems 41-60
Theorems 61-80
Theorems 81-100
Theorems 101-120
Theorems 121-140