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  • 7/29/2019 Errata: Understanding Computational Bayesian Statistics

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    Errata: Understanding Computational Bayesian

    StatisticsPage Ch. line Correction

    41 2 8 ... second envelope at the candidate value.

    44 2 24 Equation should read

    g(|y) = e12 (4)

    2

    .

    46 2 2 Equation should read

    g0() =1

    23 e1

    232(

    4)2

    51 3 10 Equation should read

    =ul

    g(|y1, . . . , yn) d .

    58 3 13-15 If it does not we reject the null hypothesis atthe level . If it does, we cannot reject the nullhypothesis and conclude 0 remains a credible value.

    59 3 13 ... credInt.

    59 3 15 Equation should read

    H0 : 0 vs. H1 : > 0

    59 3 17 ... pNull.

    59 3 29 ... credInt.

    59 3 33 ... pNull.

    cBill Bolstad 2010 1

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    Page Ch. line Correction

    60 3 9 ... credInt.

    60 3 12 Equation should read

    H0 : 0 vs. H1 : > 0

    60 3 15 ... pNull.

    60 3 24 ... credInt.

    60 3 27 Equation should read

    H0 : 0 vs. H1 : > 0

    60 3 29 ... pNull.

    71 4 7 Equation should read

    a1 (1 )b1 (1 )y

    71 4 25 ... the binomial probability of r 1 successes in r + y 1 trials.

    75 4 19 Equation should read

    f(y|) =1

    2 e1

    22 (y

    )2

    77 4 12 ... variance 2y =2

    n.

    87 4 3 It is given by.

    89 4 12-13 ...multiplied by their respective precision matrices

    92 4 16 Find the posterior mean and standard deviation of.

    cBill Bolstad 2010 2

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    Page Ch. line Correction

    103 5 9 ... previous values of the process by using ...

    103 5 13 Equation should read

    P(X(2) = x2, X(1) = x1, X

    (0) = x0) = ...

    107 5 10 This is (0) times the jth column ...

    107 5 17 Note, the ith row of the K by K identity matrix I ...

    107 5 18 ... I is the K by K identity matrix.

    124 5 26 Equation should read

    P =

    .4 .3 .2 .1

    .2 .3 .2 .3

    .3 .3 .2 .2

    .1 .3 .2 .4

    130 6 30 ... Hastings algorithm. See Chib and Greenberg (1995).

    135 6 16 Let the starting value be = .4448.

    138 6 30 Equation should read

    g(1, 2) e 1

    2(1.92)(212.912+22) .

    139 6 10 ... value (1, 2) = (2.0000, 2.0000).

    142 6 16 Equation should read

    g(1, 2) e 1

    2(1.92)(212.912+22) .

    142 6 18 Equation should read

    q2(1,

    2) e

    121.22

    ((1)22.912+(2)2) .

    146 6 9 Equation should read

    g(1, 2) e 1

    2(1.92)(212.912+22) .

    cBill Bolstad 2010 3

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    Page Ch. line Correction

    150 6 6 Equation should read

    g(1, 2) e 1

    2(1.92)(212.912+22) .

    150 6 10 Equation should read

    m2 = 1 and s22 = (1

    2) .

    154 6 6 normMixMH

    154 6 10 normMixMH

    154 6 20 normMixMH

    154 6 27 normMixMH

    155 6 3 normMixMH

    155 6 7 normMixMH

    155 6 12 Form histograms of the two samples. Do they resemble ...

    155 6 18 normMixMH

    155 6 25 normMixMH

    155 6 35 normMixMH

    cBill Bolstad 2010 4

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    Page Ch. line Correction

    156 6 2 normMixMH

    156 6 7 Form histograms of the two samples. Do they resemble ...

    156 6 13 normMixMH

    156 6 20 normMixMH

    175 7 23 normMixMH

    175 7 31 normMixMH

    176 7 7 normMixMH

    176 7 14 normMixMH

    219 9 16 Equation should read

    V11 = V10 +V

    1ML

    226 9 1 Looking at Table 9.4 ...

    226 9 26 ... are shown in Table 9.5.

    cBill Bolstad 2010 5

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    Page Ch. line Correction

    236 10 14 are the joint likelihood and the joint prior density

    239 10 4 chi-sq 11 df

    239 10 15 ...and letting = 20 + z 5 = 16.068.

    242 10 4 chi-sq 11 df

    249 10 25 ... have a sample of experimental units and that we...

    249 10 28 Equation should read

    yj =

    y1 j...

    ynj j

    .

    246 10 6 We consider the populations to be related ...

    250 10 21 We will use a multivariate normal(b0,B0)

    251 10 0 Equation should read

    m1 =1V01V1

    m0 +J1V1

    252 10 9/10 ... group means from the hypermean.

    252 10 23 ... (yj|j,, 2) is multivariate normal(j +Xj, 2I).

    255 10 11 | 2| 2.382 6.776 | 10.91 15.68 |

    259 10 9 ...or the R-function normGibbs to run ...

    261 10 8 We show that using an improper Jeffreys prior...

    cBill Bolstad 2010 6

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    Page Ch. line Correction

    308 bib. 3 Insert

    10. Chib, S., and Greenberg, E. (1995), Understanding theMetropolis-Hastings Algorithm, The American Statistician,Vol. 49, No. 4 pp. 327-335.

    and renumber rest of references

    cBill Bolstad 2010 7


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