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The QQPLOT statement creates quantile-quantile plots (Q-Q plots) and compares ordered variable values with quantiles of a specified theoretical distribution. If the data distribution matches the theoretical distribution, the points on the plot form a linear pattern. Thus, you can use a Q-Q plot to determine how well a theoretical distribution models a set of measurements.
Q-Q plots are similar to probability plots, which you can create with the PROBPLOT statement. Q-Q plots are preferable for graphical estimation of distribution parameters, whereas probability plots are preferable for graphical estimation of percentiles.
You can use any number of QQPLOT statements in the UNIVARIATE procedure. The components of the QQPLOT statement are as follows.
variables
are the variables for which Q-Q plots are created. If you specify a VAR statement, the variables must also be listed in the VAR statement. Otherwise, the variables can be any numeric variables in the input data set. If you do not specify a list of variables, then by default the procedure creates a Q-Q plot for each variable listed in the VAR statement, or for each numeric variable in the DATA= data set if you do not specify a VAR statement. For example, each of the following QQPLOT statements produces two Q-Q plots, one for Length and one for Width:
specify the theoretical distribution for the plot or add features to the plot. If you specify more than one variable, the options apply equally to each variable. Specify all options after the slash (/) in the QQPLOT statement. You can specify only one option that names the distribution in each QQPLOT statement, but you can specify any number of other options. The distributions available are the beta, exponential, gamma, lognormal, normal, two-parameter Weibull, and three-parameter Weibull. By default, the procedure produces a plot for the normal distribution.
In the following example, the NORMAL option requests a normal Q-Q plot for each variable. The MU= and SIGMA= normal-options request a distribution reference line with intercept 10 and slope 0.3 for each plot, which corresponds to a normal distribution with mean and standard deviation . The SQUARE option displays the plot in a square frame.
Table 23 lists secondary options that specify distribution parameters and control the display of a distribution reference line. Specify these options in parentheses after the distribution keyword. For example, you can request a normal Q-Q plot with a distribution reference line by specifying the NORMAL option as follows:
The following entries provide detailed descriptions of options in the QQPLOT statement. Options marked with † apply only when traditional graphics are produced. For detailed descriptions of options common to all plot statements, see the section Dictionary of Common Options.
ALPHA=value-list|EST
specifies the mandatory shape parameter for quantile plots that are requested by the BETA, GAMMA, PARETO, and POWER options. Enclose the ALPHA= option in parentheses after the distribution keyword. If you specify ALPHA=EST, a maximum likelihood estimate is computed for .
creates a beta quantile plot for each combination of the required shape parameters and , which are specified by the required ALPHA= and BETA= beta-options. If you specify ALPHA=EST and BETA=EST, the procedure creates a plot based on maximum likelihood estimates for and . You can specify the SCALE= beta-option as an alias for the SIGMA= beta-option and the THRESHOLD= beta-option as an alias for the THETA= beta-option. To create a plot that is based on maximum likelihood estimates for and , specify ALPHA=EST and BETA=EST. For more information, see the section Beta Distribution.
To obtain graphical estimates of and , specify lists of values in the ALPHA= and BETA= beta-options and select the combination of and that most nearly linearizes the point pattern. To assess the point pattern, you can add a diagonal distribution reference line that corresponds to lower threshold parameter and scale parameter by specifying the THETA= and SIGMA= beta-options. Alternatively, you can add a line that corresponds to estimated values of and by specifying the THETA=EST and SIGMA=EST beta-options. Agreement between the reference line and the point pattern indicates that the beta distribution with parameters , , , and is a good fit.
BETA=value-list|EST
B=value|EST
specifies the mandatory shape parameter for quantile plots that are requested by the BETA option. Enclose the BETA= option in parentheses after the BETA option. If you specify BETA=EST, a maximum likelihood estimate is computed for .
C=value-list|EST
specifies the shape parameter c for quantile plots that are requested by the WEIBULL and WEIBULL2 options. Enclose this option in parentheses after the WEIBULL or WEIBULL2 option. C= is a required Weibull-option in the WEIBULL option; in this situation, it accepts a list of values, or if you specify C=EST, a maximum likelihood estimate is computed for c. You can optionally specify C=value or C=EST as a Weibull2-option with the WEIBULL2 option to request a distribution reference line; in this situation, you must also specify the SIGMA=value or SIGMA=EST Weibull2-option.
† CGRID=color
specifies the color for grid lines when a grid is displayed on the plot in traditional graphics. This option also produces a grid if the GRID= option is not specified.
creates an exponential quantile plot. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and SIGMA= exponential-options. Alternatively, you can add a line that corresponds to estimated values of the threshold parameter and the scale parameter by specifying THETA=EST and SIGMA=EST the exponential-options. Agreement between the reference line and the point pattern indicates that the exponential distribution with parameters and is a good fit. You can specify the SCALE= exponential-option as an alias for the SIGMA= exponential-option and the THRESHOLD= exponential-option as an alias for the THETA= exponential-option. For more information, see the section Exponential Distribution.
GAMMA(ALPHA=value|EST <gamma-options>)
creates a gamma quantile plot for each value of the shape parameter that is specified in the mandatory ALPHA= gamma-option. If you specify ALPHA=EST, the procedure creates a plot that is based on a maximum likelihood estimate for . To obtain a graphical estimate of , specify a list of values for the ALPHA= gamma-option and select the value that most nearly linearizes the point pattern. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and SIGMA= gamma-options. Alternatively, you can add a line that corresponds to estimated values of the threshold parameter and the scale parameter by specifying the THETA=EST and SIGMA=EST gamma-options. Agreement between the reference line and the point pattern indicates that the gamma distribution with parameters , , and is a good fit. You can specify the SCALE= gamma-option as an alias for the SIGMA= gamma-option and the THRESHOLD= gamma-option as an alias for the THETA= gamma-option. For more information, see the section Gamma Distribution.
GRID
displays a grid of horizontal lines that are positioned at major tick marks on the vertical axis.
GUMBEL<(Gumbel-options)>
creates a Gumbel quantile plot. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the MU= and SIGMA= Gumbel-options. Alternatively, you can add a line that corresponds to estimated values of the location parameter and the scale parameter by specifying MU=EST and SIGMA=EST the Gumbel-options. Agreement between the reference line and the point pattern indicates that the exponential distribution with parameters and is a good fit. For more information, see the section Gumbel Distribution.
† LGRID=linetype
specifies the line type for the grid when a grid is displayed on the plot. This option also creates a grid if the GRID option is not specified. By default, LGRID=1, which produces a solid line.
creates a lognormal quantile plot for each value of the shape parameter that is specified in the mandatory SIGMA= lognormal-option. If you specify SIGMA=EST, the procedure creates a plot that is based on an estimate for , which is computed as described in the section Lognormal Distribution. To obtain a graphical estimate of , specify a list of values for the SIGMA= lognormal-option and select the value that most nearly linearizes the point pattern. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and ZETA= lognormal-options. Alternatively, you can add a line that corresponds to estimated values of the threshold parameter and the scale parameter by specifying the THETA=EST and ZETA=EST lognormal-options. Agreement between the reference line and the point pattern indicates that the lognormal distribution with parameters , , and is a good fit. You can specify the THRESHOLD= lognormal-option as an alias for the THETA= lognormal-option and the SCALE= lognormal-option as an alias for the ZETA= lognormal-option. For more information, see the section Lognormal Distribution. See Example 3.31 through Example 3.33 for examples that use the LOGNORMAL option.
MU=value|EST
specifies the mean for a quantile plot that is requested by the GUMBEL and NORMAL options. Enclose MU= in parentheses after the distribution keyword. You can specify MU=EST to request a distribution reference line with equal to the sample mean with the normal distribution. If you specify MU=EST for the Gumbel distribution, the procedure computes a maximum likelihood estimate.
NADJ=value
specifies the adjustment value to add to the sample size in the calculation of theoretical percentiles. By default, NADJ=. For more information, see to Chambers et al. (1983).
NOLINELEGEND
NOLEGEND
suppresses the legend for the optional distribution reference line. This option applies only to ODS Graphics output.
NORMAL<(normal-options)>
creates a normal quantile plot. This is the default if you omit a distribution option. To assess the point pattern, you can add a diagonal distribution reference line that corresponds to and by specifying the MU= and SIGMA= normal-options. Alternatively, you can add a line that corresponds to estimated values of and by specifying the MU=EST and SIGMA=EST normal-options; the estimates of the mean and the standard deviation are the sample mean and sample standard deviation. Agreement between the reference line and the point pattern indicates that the normal distribution with parameters and is a good fit. For more information, see the section Normal Distribution. See Example 3.28 and Example 3.30 for examples that use the NORMAL option.
PARETO(ALPHA=value|EST <Pareto-options>)
creates a generalized Pareto quantile plot for each value of the shape parameter that is specified in the mandatory ALPHA= Pareto-option. If you specify ALPHA=EST, the procedure creates a plot that is based on a maximum likelihood estimate for . To obtain a graphical estimate of , specify a list of values for the ALPHA= Pareto-option and select the value that most nearly linearizes the point pattern. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and SIGMA= Pareto-options. Alternatively, you can add a line that corresponds to estimated values of the threshold parameter and the scale parameter by specifying the THETA=EST and SIGMA=EST Pareto-options. Agreement between the reference line and the point pattern indicates that the generalized Pareto distribution with parameters , , and is a good fit. For more information, see the section Generalized Pareto Distribution.
PCTLAXIS<(axis-options)>
adds a nonlinear percentile axis along the frame of the Q-Q plot opposite the theoretical quantile axis. The added axis is identical to the axis for probability plots that are produced by the PROBPLOT statement. When you specify this option, you must also specify values for the HREF= option in quantile units, and you cannot specify the NOFRAME option. You can specify the following axis-options:
† CGRID=color
specifies the color of grid lines that are associated with the percentile axis.
GRID
draws grid lines perpendicular to the percentile axis at major tick marks.
LABEL='string'
specifies the label for the percentile axis.
† LGRID=linetype
specifies the line type to use for grid lines that are associated with the percentile axis.
PCTLORDER=value-list
specifies the tick mark values to be labeled on the percentile axis. The values must be listed in increasing order and must be between 0 and 100, exclusive. Values that correspond to quantiles outside the range of the theoretical quantile axis are not displayed.
† WGRID=n
specifies the thickness of grid lines that are associated with the percentile axis.
† PCTLMINOR
requests minor tick marks for the percentile axis when you specify the PCTLAXIS option. The HMINOR option overrides the PCTLMINOR option.
PCTLSCALE
requests scale labels for the theoretical quantile axis in percentile units, resulting in a nonlinear axis scale. Tick marks are drawn uniformly across the axis based on the quantile scale. In all other respects, the plot remains the same, and you must specify values for the HREF= option in quantile units. For a true nonlinear axis, use the PCTLAXIS option or use the PROBPLOT statement.
POWER(ALPHA=value|EST <power-options>)
creates a power function quantile plot for each value of the shape parameter that is specified in the mandatory ALPHA= power-option. If you specify ALPHA=EST, the procedure creates a plot based on a maximum likelihood estimate for . To obtain a graphical estimate of , specify a list of values for the ALPHA= power-option and select the value that most nearly linearizes the point pattern. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and SIGMA= power-options. Alternatively, you can add a line that corresponds to estimated values of the threshold parameter and the scale parameter by specifying the THETA=EST and SIGMA=EST power-options. Agreement between the reference line and the point pattern indicates that the power function distribution with parameters , , and is a good fit. For more information, see the section Power Function Distribution.
RAYLEIGH<(Rayleigh-options)>
creates a Rayleigh quantile plot. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and SIGMA= Rayleigh-options. Alternatively, you can add a line that corresponds to estimated values of the threshold parameter and the scale parameter by specifying the THETA=EST and SIGMA=EST Rayleigh-options. Agreement between the reference line and the point pattern indicates that the exponential distribution with parameters and is a good fit. For more information, see the section Rayleigh Distribution.
RANKADJ=value
specifies the adjustment value to add to the ranks in the calculation of theoretical percentiles. By default, RANKADJ=, as recommended by Blom (1958). For more information, see Chambers et al. (1983).
ROTATE
switches the horizontal and vertical axes so that the theoretical quantiles are plotted vertically and the data are plotted horizontally. Regardless of whether the plot has been rotated, horizontal axis options (such as HAXIS=) still refer to the horizontal axis, and vertical axis options (such as VAXIS=) still refer to the vertical axis. All other options that depend on axis placement adjust to the rotated axes.
SIGMA=value|EST
specifies the parameter , where . Alternatively, you can specify SIGMA=EST to request an estimate for , which is computed as described in the section Lognormal Distribution. The interpretation and use of the SIGMA= option depend on the distribution option with which it is used, as summarized in Table 25. Enclose this option in parentheses after the distribution option.
Table 25: Uses of the SIGMA= Option
Distribution Option
Use of the SIGMA= Option
BETA EXPONENTIAL GAMMA PARETO POWER RAYLEIGH WEIBULL
THETA= and SIGMA= request a distribution reference line that corresponds to and .
GUMBEL
MU= and SIGMA= request a distribution reference line that corresponds to and .
LOGNORMAL
SIGMA= requests n quantile plots with shape parameters . The SIGMA= option must be specified.
NORMAL
MU= and SIGMA= request a distribution reference line that corresponds to and . SIGMA=EST requests a line with equal to the sample standard deviation.
WEIBULL2
SIGMA= and C= request a distribution reference line that corresponds to and .
SLOPE=value|EST
specifies the slope for a distribution reference line that is requested by the LOGNORMAL or WEIBULL2 option. Enclose the SLOPE= option in parentheses after the distribution option. When you use the SLOPE= lognormal-option with the LOGNORMAL option, you must also specify a threshold parameter value in the THETA= lognormal-option to request the line. The SLOPE= lognormal-option is an alternative to the ZETA= lognormal-option for specifying , because the slope is equal to .
When you use the SLOPE= Weibull2-option (in the WEIBULL2 option), you must also specify a scale parameter value in the SIGMA= Weibull2-option to request the line. The SLOPE= Weibull2-option is an alternative to the C= Weibull2-option for specifying , because the slope is equal to .
For example, the first and second QQPLOT statements produce the same quantile plots and the third and fourth QQPLOT statements produce the same quantile plots:
displays the quantile plot in a square frame. (By default, the frame is rectangular.)
THETA=value|EST
THRESHOLD=value|EST
specifies the lower threshold parameter for plots that are requested by the BETA, EXPONENTIAL, GAMMA, PARETO, POWER, RAYLEIGH, LOGNORMAL, WEIBULL, and WEIBULL2 options. Enclose the THETA= option in parentheses after a distribution option. When used with the WEIBULL2 option, the THETA= option specifies the known lower threshold , for which the default is 0. When used with the other distribution options, the THETA= option specifies for a distribution reference line; alternatively in this situation, you can specify THETA=EST to request a maximum likelihood estimate for . To request the line, you must also specify a scale parameter.
creates a three-parameter Weibull quantile plot for each value of the required shape parameter c, which is specified in the mandatory C= Weibull-option. To create a plot that is based on a maximum likelihood estimate for c, specify C=EST. To obtain a graphical estimate of c, specify a list of values in the C= Weibull-option and select the value that most nearly linearizes the point pattern. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the THETA= and SIGMA= Weibull-options. Alternatively, you can add a line that corresponds to estimated values of and by specifying the THETA=EST and SIGMA=EST Weibull-options. Agreement between the reference line and the point pattern indicates that the Weibull distribution with parameters c, , and is a good fit. You can specify the SCALE= Weibull-option as an alias for the SIGMA= Weibull-option and the THRESHOLD= Weibull-option as an alias for the THETA= Weibull-option. See Example 3.34.
creates a two-parameter Weibull quantile plot. You should use the WEIBULL2 option when your data have a known lower threshold , which is 0 by default. To specify the threshold value , use the THETA= Weibull2-option, whose default is 0. An advantage of the two-parameter Weibull plot over the three-parameter Weibull plot is that the parameters c and can be estimated from the slope and intercept of the point pattern. A disadvantage is that the two-parameter Weibull distribution applies only in situations where the threshold parameter is known. To obtain a graphical estimate of , specify a list of values for the THETA= Weibull2-option and select the value that most nearly linearizes the point pattern. To assess the point pattern, add a diagonal distribution reference line that corresponds to and by specifying the SIGMA= and C= Weibull2-options. Alternatively, you can add a distribution reference line that corresponds to estimated values of and by specifying the SIGMA=EST and C=EST Weibull2-options. Agreement between the reference line and the point pattern indicates that the Weibull distribution with parameters , , and is a good fit. You can specify the SCALE= Weibull2-option as an alias for the SIGMA= Weibull2-option and the SHAPE= Weibull2-option as an alias for the C= Weibull2-option. See Example 3.34.
† WGRID=n
specifies the line thickness for the grid when traditional graphics are produced. This option does not apply to ODS Graphics output.
ZETA=value|EST
specifies a value for the scale parameter for the lognormal quantile plots that are requested by the LOGNORMAL option. Enclose the ZETA= lognormal-option in parentheses after the LOGNORMAL option. To request a distribution reference line with intercept and slope , specify the THETA= and ZETA= suboptions.