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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

 

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