Module Import alias identifier ImportFrom alias ImportFrom alias FunctionDef arguments args NameParam NameParam defaults Num body Expr Str Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad NameLoad Expr Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad TryExcept body Assign NameStore SubscriptLoad SubscriptLoad Call NameLoad Call NameLoad NameLoad NameLoad Index Num Index Num handlers ExceptHandler type NameLoad body Assign NameStore AttributeLoad NameLoad attr Return NameLoad decorator_list Call NameLoad keyword Str FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam defaults Num Num Str body Expr Str Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad NameLoad Expr Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad TryExcept body Assign NameStore SubscriptLoad Call NameLoad Call NameLoad NameLoad NameLoad NameLoad NameLoad NameLoad Index Num handlers ExceptHandler type NameLoad body Assign NameStore TupleLoad AttributeLoad NameLoad attr AttributeLoad NameLoad attr Return NameLoad decorator_list Call NameLoad keyword Str FunctionDef arguments args NameParam defaults body Expr Str Return Call AttributeLoad NameLoad attr Call AttributeLoad NameLoad attr AttributeLoad NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults Num body Expr Str If CompareLtE NameLoad Num body Raise Call NameLoad Str For TupleStore NameStore NameStore NameStore NameStore Call NameLoad NameLoad NameLoad body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Num Assign NameStore BinOpDiv BinOpSub NameLoad Num NameLoad Expr Yield TupleLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore Call NameLoad Assign NameStore Call NameLoad NameLoad For TupleStore NameStore NameStore Call NameLoad NameLoad body If CompareIn NameLoad NameLoad body Continue orelse Expr Call AttributeLoad NameLoad attr NameLoad Assign NameStore Num Assign NameStore BinOpAdd NameLoad Num While BoolOpAnd CompareLt NameLoad NameLoad CompareLt NameLoad NameLoad body If CompareNotIn SubscriptLoad NameLoad Index NameLoad NameLoad body AugAssignAdd NameStore Num AugAssignAdd NameStore Num Assign NameStore BinOpSub BinOpSub NameLoad NameLoad Num Assign NameStore NameLoad If BoolOpOr UnaryOpNot NameLoad CompareLt NameLoad NameLoad body Return Expr Yield TupleLoad NameLoad Call NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam defaults Num Num Str body Expr Str For TupleStore NameStore NameStore NameStore NameStore Call NameLoad NameLoad NameLoad body Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad Num Expr Yield Call NameLoad NameLoad NameLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam defaults Num Num Str body Expr Str Assign NameStore Call NameLoad NameLoad Num If CompareEq NameLoad Str body If CompareNotEq NameLoad Num body Raise Call NameLoad Str If CompareNotIn NameLoad NameLoad body Raise Call NameLoad Str Return TupleLoad Num BinOpDiv SubscriptLoad NameLoad Index NameLoad NameLoad orelse If CompareEq NameLoad Str body If CompareNotEq NameLoad Num body Raise Call NameLoad Str If CompareNotIn NameLoad NameLoad body Raise Call NameLoad Str Return TupleLoad BinOpDiv SubscriptLoad NameLoad Index NameLoad NameLoad Num Assign NameStore Call NameLoad NameLoad NameLoad NameLoad If CompareEq NameLoad Str body Assign NameStore SubscriptLoad NameLoad Index Num orelse If CompareEq NameLoad Str body Assign NameStore SubscriptLoad NameLoad Index Num orelse Raise Call NameLoad BinOpMod Str NameLoad Assign NameStore BinOpDiv BinOpMult NameLoad NameLoad NameLoad Assign NameStore BinOpDiv NameLoad NameLoad If CompareGt NameLoad Num body Assign NameStore Num Return TupleLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults body Expr Str Assign NameStore NameLoad Assign NameStore NameLoad If CompareIn TupleLoad NameLoad NameLoad NameLoad NameLoad body Return SubscriptLoad NameLoad Index TupleLoad NameLoad NameLoad NameLoad If BoolOpAnd CompareEq NameLoad Num CompareLtE NameLoad Num body If BoolOpAnd CompareIn NameLoad NameLoad CompareLt NameLoad Call NameLoad SubscriptLoad NameLoad Index NameLoad body Assign TupleStore NameStore NameStore SubscriptLoad SubscriptLoad NameLoad Index NameLoad Index NameLoad If BoolOpOr CompareIs NameLoad NameLoad CompareIs NameLoad NameLoad body Raise Call NameLoad BinOpMod Str TupleLoad NameLoad NameLoad NameLoad Return TupleLoad NameLoad NameLoad decorator_list Assign NameStore Dict Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Assign NameStore Dict Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Num Assign NameStore Dict TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num Assign NameStore ListLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num Assign NameStore ListLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num Assign NameStore ListLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad NameLoad NameLoad TupleLoad Num Num Assign NameStore Dict Num Num Num NameLoad NameLoad NameLoad
N/A N/A numpy np skbio.diversity._util _validate_counts_vector skbio.util._decorator experimental lladser_pe N/A N/A counts r N/A 10 N/A N/A Calculate single point estimate of conditional uncovered probability.

    Parameters
    ----------
    counts : 1-D array_like, int
        Vector of counts.
    r : int, optional
        Number of new colors that are required for the next prediction.

    Returns
    -------
    double
        Single point estimate of the conditional uncovered probability. May be
        ``np.nan`` if a point estimate could not be computed.

    See Also
    --------
    lladser_ci

    Notes
    -----
    This function is just a wrapper around the full point estimator described
    in Theorem 2 (i) in [1]_, intended to be called for a single best estimate
    on a complete sample. This function is not guaranteed to return estimated
    uncovered probabilities less than 1 if the coverage is too low.

    References
    ----------
    .. [1] Lladser, Gouet, and Reeder, "Extrapolation of Urn Models via
       Poissonization: Accurate Measurements of the Microbial Unknown" PLoS
       2011.

     N/A counts N/A _validate_counts_vector counts N/A sample N/A _expand_counts counts N/A N/A N/A N/A np random shuffle sample N/A N/A N/A pe N/A N/A N/A list N/A _lladser_point_estimates sample r N/A -1 N/A 0 N/A N/A N/A IndexError N/A N/A pe N/A np nan N/A pe N/A N/A experimental as_of 0.4.0 lladser_ci N/A N/A counts r alpha f ci_type N/A 0.95 10 ULCL N/A N/A Calculate single CI of the conditional uncovered probability.

    Parameters
    ----------
    counts : 1-D array_like, int
        Vector of counts.
    r : int
        Number of new colors that are required for the next prediction.
    alpha : float, optional
        Desired confidence level.
    f : float, optional
        Ratio between upper and lower bound.
    ci_type : {'ULCL', 'ULCU', 'U', 'L'}
        Type of confidence interval. If ``'ULCL'``, upper and lower bounds with
        conservative lower bound. If ``'ULCU'``, upper and lower bounds with
        conservative upper bound. If ``'U'``, upper bound only, lower bound
        fixed to 0.0. If ``'L'``, lower bound only, upper bound fixed to 1.0.

    Returns
    -------
    tuple
        Confidence interval as ``(lower_bound, upper_bound)``.

    See Also
    --------
    lladser_pe

    Notes
    -----
    This function is just a wrapper around the full CI estimator described
    in Theorem 2 (iii) in [1]_, intended to be called for a single best CI
    estimate on a complete sample.

    References
    ----------
    .. [1] Lladser, Gouet, and Reeder, "Extrapolation of Urn Models via
       Poissonization: Accurate Measurements of the Microbial Unknown" PLoS
       2011.

     N/A counts N/A _validate_counts_vector counts N/A sample N/A _expand_counts counts N/A N/A N/A N/A np random shuffle sample N/A N/A N/A ci N/A N/A list N/A _lladser_ci_series sample r alpha f ci_type N/A -1 N/A N/A N/A IndexError N/A N/A ci N/A N/A np nan N/A np nan N/A ci N/A N/A experimental as_of 0.4.0 _expand_counts N/A N/A counts N/A N/A N/A Convert vector of counts at each index to vector of indices. N/A N/A N/A np repeat N/A N/A np arange N/A counts size counts N/A _lladser_point_estimates N/A N/A sample r N/A 10 N/A N/A Series of point estimates of the conditional uncovered probability.

    Parameters
    ----------
    sample : 1-D array_like, int
        Series of random observations.
    r : int, optional
        Number of new colors that are required for the next prediction.

    Returns
    -------
    generator
        Each new color yields a tuple of three elements: the point estimate,
        position in sample of prediction, and random variable from Poisson
        process (mostly to make testing easier).

    Raises
    ------
    ValueError
        If `r` is less than or equal to 2.

    Notes
    -----
    This is the point estimator described in Theorem 2 (i) in [1]_.

    References
    ----------
    .. [1] Lladser, Gouet, and Reeder, "Extrapolation of Urn Models via
       Poissonization: Accurate Measurements of the Microbial Unknown" PLoS
       2011.

     N/A N/A r 2 N/A N/A N/A ValueError r must be greater than or equal to 3. N/A N/A count seen cost i N/A _get_interval_for_r_new_otus sample r N/A N/A t N/A N/A N/A np random gamma count 1 N/A point_est N/A N/A r 1 t N/A N/A N/A point_est i t N/A _get_interval_for_r_new_otus N/A N/A seq r N/A N/A N/A Compute interval between r new OTUs for seq of samples.

    Imagine an urn with colored balls. Given a drawing of balls from the urn,
    compute how many balls need to be looked at to discover r new colors.
    Colors can be repeated.

    Parameters
    ----------
    seq : sequence
        Series of observations (the actual sample, not the frequencies).
    r : int
        Number of new colors that need to be observed for a new interval.

    Returns
    -------
    generator
        For each new color seen for the first time, yields a tuple of four
        elements: the length of interval (i.e. number of observations looked
        at), the set of seen colors, position in seq after seeing last new
        color (end of interval), and position in seq where interval is started.

     N/A seen N/A set N/A seq_len N/A len seq N/A N/A i curr N/A enumerate seq N/A N/A N/A curr seen N/A N/A N/A N/A N/A N/A seen add curr N/A unseen 0 N/A j N/A i 1 N/A N/A N/A unseen r N/A j seq_len N/A N/A N/A N/A seq N/A j seen N/A N/A unseen 1 N/A j 1 N/A count N/A N/A j i 1 N/A cost j N/A N/A N/A count N/A unseen r N/A N/A N/A N/A N/A count N/A set seen cost i N/A _lladser_ci_series N/A N/A seq r alpha f ci_type N/A 0.95 10 ULCL N/A N/A Construct r-color confidence intervals for uncovered conditional prob.

    Parameters
    ----------
    seq : sequence
        Sequence of colors (the actual sample, not the counts).
    r : int
        Number of new colors that are required for the next prediction.
    alpha : float, optional
        Desired confidence level.
    f : float, optional
        Ratio between upper and lower bound.
    ci_type : {'ULCL', 'ULCU', 'U', 'L'}
        Type of confidence interval. If ``'ULCL'``, upper and lower bounds with
        conservative lower bound. If ``'ULCU'``, upper and lower bounds with
        conservative upper bound. If ``'U'``, upper bound only, lower bound
        fixed to 0.0. If ``'L'``, lower bound only, upper bound fixed to 1.0.

    Returns
    -------
    generator
        Yields one CI prediction for each new color that is detected and where.

     N/A N/A count seen cost i N/A _get_interval_for_r_new_otus seq r N/A N/A t N/A N/A N/A np random gamma count 1 N/A N/A N/A _lladser_ci_from_r r t alpha f ci_type N/A _lladser_ci_from_r N/A N/A r t alpha f ci_type N/A 0.95 10 ULCL N/A N/A Construct r-color confidence interval for uncovered conditional prob.

    Returns
    -------
    tuple
        Confidence interval that contains the true conditional uncovered
        probability with a probability of 100% * `alpha`.

    Raises
    ------
    ValueError
        For combinations of `r`, `f`, and `alpha` that do not have precomputed
        results.

     N/A alpha N/A round alpha 2 N/A N/A ci_type U N/A N/A N/A alpha 0.95 N/A N/A N/A ValueError alpha must be 0.95 if ci_type is 'U'. N/A N/A r _UPPER_CONFIDENCE_BOUND N/A N/A N/A ValueError r must be between 1-25 or 50 if ci_type is 'U'. N/A N/A 0.0 N/A N/A _UPPER_CONFIDENCE_BOUND N/A r t N/A N/A N/A ci_type L N/A N/A N/A alpha 0.95 N/A N/A N/A ValueError alpha must be 0.95 if ci_type is 'L'. N/A N/A r _LOWER_CONFIDENCE_BOUND N/A N/A N/A ValueError r must be between 1-25 if ci_type is 'L'. N/A N/A N/A N/A _LOWER_CONFIDENCE_BOUND N/A r t 1.0 N/A bound_params N/A _ul_confidence_bounds f r alpha N/A N/A ci_type ULCL N/A N/A bound_param N/A bound_params N/A 0 N/A N/A N/A ci_type ULCU N/A N/A bound_param N/A bound_params N/A 1 N/A N/A N/A ValueError N/A Unknown ci_type '%s'. ci_type N/A upper_bound N/A N/A bound_param f t N/A lower_bound N/A bound_param t N/A N/A upper_bound 1 N/A N/A upper_bound 1.0 N/A N/A lower_bound upper_bound N/A _ul_confidence_bounds N/A N/A f r alpha N/A N/A N/A Return confidence bounds based on ratio and alpha.

    This function is just a lookup of some precomputed values.

    Parameters
    ----------
    f : float
        Desired ratio of upper to lower bound.
    r : int
        Number of new colors.
    alpha : float
        Confidence interval (for 95% confidence use 0.95).

    Returns
    -------
    tuple
        Constants ``(c_1, c_2)`` such that the confidence interval is
        ``[c_1/T_r, c_1*f/T_r]`` for conservative lower bound intervals and
        ``[c_2/T_r, c_2*f/T_r]`` for conservative upper bound intervals.

     N/A a None N/A b None N/A N/A N/A f r alpha _PRECOMPUTED_TABLE N/A N/A N/A _PRECOMPUTED_TABLE N/A N/A f r alpha N/A N/A N/A f 10 N/A r 50 N/A N/A N/A N/A alpha _CBS N/A r N/A len N/A _CBS N/A alpha N/A N/A N/A a b N/A N/A _CBS N/A alpha N/A r N/A N/A N/A a None N/A b None N/A N/A N/A ValueError N/A No constants are precomputed for the combination of f=%f, r=%d, and alpha=%.2f N/A f r alpha N/A N/A a b N/A N/A _UPPER_CONFIDENCE_BOUND N/A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 50 2.995732274 4.743864518 6.295793622 7.753656528 9.153519027 10.51303491 11.84239565 13.1481138 14.43464972 15.70521642 16.96221924 18.20751425 19.44256933 20.66856908 21.88648591 23.09712976 24.30118368 25.49923008 26.69177031 27.87923964 29.06201884 30.24044329 31.41481021 32.58538445 33.75240327 62.1710567 N/A _LOWER_CONFIDENCE_BOUND N/A 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 0.051293294 0.35536151 0.817691447 1.366318397 1.970149568 2.613014744 3.285315692 3.980822786 4.69522754 5.425405697 6.169007289 6.924212514 7.689578292 8.463937522 9.246330491 10.03595673 10.83214036 11.63430451 12.44195219 13.2546516 14.07202475 14.89373854 15.71949763 16.54903871 17.38212584 N/A _PRECOMPUTED_TABLE N/A N/A 2 50 0.95 N/A 2 33 0.95 N/A 1.5 100 0.95 N/A 1.5 94 0.95 N/A 2.5 19 0.95 N/A 80 2 0.95 N/A 48 2 0.95 N/A 40 2 0.95 N/A 24 2 0.95 N/A 20 3 0.95 N/A 12 3 0.95 N/A 10 4 0.95 N/A 6 6 0.95 N/A 5 7 0.95 N/A 3 14 0.95 N/A 2.5 19 0.95 N/A 1.5 94 0.95 N/A 1.25 309 0.95 N/A 31.13026306 38.94718565 N/A 22.3203508 23.4487304 N/A 79.0424349 83.22790086 N/A 75.9077267 76.5492088 N/A 11.26109001 11.96814857 N/A 0.0598276655 0.35536151 N/A 0.1013728884 0.355358676 N/A 0.1231379857 0.355320458 N/A 0.226833483 0.346045204 N/A 0.320984257 0.817610455 N/A 0.59024303 0.78772161 N/A 0.806026244 1.360288674 N/A 1.8207383 2.58658608 N/A 2.4830393 3.22806682 N/A 7.17185045 8.27008349 N/A 11.26109001 11.96814857 N/A 75.9077267 76.5492088 N/A 275.661191 275.949782 N/A _CB_90 N/A N/A None None N/A None None N/A None None N/A 0.5635941995 1.0958347 N/A 0.6764656264 1.744588615 N/A 0.8018565594 2.432587343 N/A 0.9282215025 3.151897973 N/A 1.053433716 3.894766804 N/A 1.177158858 4.656118177 N/A 1.299491033 5.432468058 N/A 1.420604842 6.221304605 N/A 1.540665805 7.020746595 N/A 1.659812701 7.829342026 N/A 1.778158703 8.645942495 N/A 1.895796167 9.469621185 N/A 2.012801198 10.29961731 N/A 2.129237257 11.13529724 N/A 2.245157877 11.97612664 N/A 2.360608695 12.82164994 N/A 2.475628991 13.67147502 N/A 2.590252861 14.52526147 N/A 2.704510123 15.38271151 N/A 2.818427036 16.2435629 N/A 2.932026869 17.10758326 N/A 3.045330351 17.97456551 N/A 3.15835605 18.8443242 N/A None None N/A None None N/A None None N/A None None N/A 3.719850286 23.22944415 N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 4.828910181 32.13892224 N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 5.924900191 41.17906791 N/A _CB_95 N/A N/A None None N/A None None N/A None None N/A None None N/A 0.8060262438 1.360288674 N/A 0.9240311584 1.969902537 N/A 1.053998892 2.613007253 N/A 1.185086998 3.285315518 N/A 1.315076337 3.980822783 N/A 4.69522754 4.695227541 N/A 1.570546801 5.425405698 N/A 1.696229569 6.169007289 N/A 1.820753729 6.924212513 N/A 1.944257622 7.689578291 N/A 2.066857113 8.463937522 N/A 2.188648652 9.246330491 N/A 2.309712994 10.03595673 N/A 2.430118373 10.83214036 N/A 2.54992301 11.63430451 N/A 2.669177032 12.44195219 N/A 2.787923964 13.2546516 N/A 2.906201884 14.07202475 N/A 3.024044329 14.89373854 N/A 3.14148102 15.71949763 N/A 3.258538445 16.54903871 N/A 3.375240327 17.38212584 N/A None None N/A None None N/A None None N/A None None N/A 3.95409722 21.59397923 N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 5.093973695 30.19573919 N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 6.217105673 38.96473258 N/A _CB_99 N/A N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 1.36031629 1.768978323 N/A 1.470856924 2.329171347 N/A 1.604478487 2.906049304 N/A 1.741759456 3.507452949 N/A 1.878809285 4.130199076 N/A 2.014632329 4.771246173 N/A 2.149044735 5.428180734 N/A 2.282101533 6.09907346 N/A 2.413917374 6.782354878 N/A 2.544610844 7.476728267 N/A 2.674289153 8.181107778 N/A 2.803045614 8.894573463 N/A 2.930960779 9.616337916 N/A 3.058104355 10.34572103 N/A 3.184536992 11.08213063 N/A 3.310311816 11.82504734 N/A 3.435475649 12.57401269 N/A 3.560070013 13.32861956 N/A 3.684131925 14.08850448 N/A 3.807694563 14.85334135 N/A None None N/A None None N/A None None N/A None None N/A 4.41897094 18.7424258 N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 5.61643962 26.7700386 N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A None None N/A 6.79033616 35.0324474 N/A _CBS N/A 0.9 0.95 0.99 _CB_90 _CB_95 _CB_99