Validation Estimation Editor

Use this option to perform validation checks on your block model estimations. You can perform either a cross validation or jackknife check.

When you perform a Cross Validation, the results are not written to the block model. Instead, a grade estimation is performed at each sample point, while ignoring the data value at that sample point. The resulting estimates are written to a nominated mapfile for analysis. Areas where the estimated value differs significantly from the actual value may be areas that should receive extra attention. A large difference may indicate that the grade estimation process does not have enough data to provide reliable estimates.

Jackknife estimates bias and variance. How similar or different grades are of samples in one dataset from the nearest sample in another dataset is the basic answer sought with Jackknife. A basic condition is that both datasets are defined within the same geological domain. The first dataset may be exploration drillhole samples and the second dataset might be production blasthole samples. Alternatively, both datasets may be exploration samples with the same field grade (Au, Cu, etc.) but different drillhole type, or different drilling contractor, etc.

Instructions

On the Block menu, point to Grade Estimation, and then click Validation Estimation Editor.

Sample Selection

Use this panel to enter the basic information about your project. You will select the database, block model, and estimation method here.

Follow these steps:

Enter a name for the Estimation file, or select it from the drop-down list. The drop-down list displays all files found in the current working directory that have the (.bef) extension. Click Browse to select a file from another location.

Tip
You can make changes to an existing estimation file, then click the Save As icon to save the edited version under a new name. This allows you to transfer all the parameter settings from the Estimation Editor to the new file without having to enter everything in again.
Enter or select an Estimation ID. To create a new estimation ID, click the New icon as shown below, and provide a unique name for the current panel settings. Up to nine separate IDs can be created for each BEF file.

Figure 1 : Click to create a new estimation ID.

Setting up multiple estimation passes

Click the Estimation Passes icon located at the top of the panel, as shown below.

Tip: This should be done after you have completed the main panel entries for the initial estimation pass.

Figure 2 : Estimation Editor Passes Configuration panel.

The Passes Configuration panel uses tabs that divide the input sections into five separate areas: Search Region, Sample Count, Sample Limit, High Yield Limits, and Soft Boundaries. However, you can view all of the input sections as one large table by clicking the Show All Columns button.

The greyed-out fields show the values in place from the main panel. These cannot be edited.

In Search Region, you can either set an Increasing Factor to automatically calculate a new value for each successive pass, or type a value directly into the table cells.

Example: A value of 2 will increase each successive pass by a factor of 2. If the initial pass has a Major value of 100, then the second pass will have a value of 200, the third pass will have a value of 400, the fourth pass will have a value of 800, etc.

Enter the number of passes you want by typing into the Passes field, or by using the slider.

In High Yield Limits, enter a Reduction Factor between 0 and 1. This represents the percentage that the search radius will be reduced.

The ID Description is optional and is not required. However, they can be very helpful, especially when you are creating multiple IDs.

If you need to edit these fields you may do so by clicking the icon to open the estimation file options, then make your changes.

Figure 3 : Click to open the estimation file Options panel.

Figure 4 : Estimation ID Options panel.

Run

Select this option to perform an estimation using the highlighted estimation ID. This option can only be used to perform a single estimation run. As a result, this option will be unavailable when multiple IDs have been highlighted. If you want to run multiple estimation jobs, use the Batch option instead.

Delete

Select this option to delete the highlighted estimation ID. Once selected, you will need to confirm the deletion before the estimation parameters are removed from the associated block estimation file.

Rename/Change Description

Select this option to rename the highlighted estimation ID. Once selected, the Rename estimation panel displays. Enter the new estimation ID. Select OK to assign the new estimation ID.

Properties

Select this option to display the estimation parameters for the highlighted estimation ID. Once selected, a properties window displays.

Batch

Select this option to run multiple estimation jobs using the highlighted estimation IDs. Once selected, the Batch panel displays.

Figure 5 : Batch panel.

The estimations will be run in the order that they appear in the list. You can edit the order by highlighting an ID, then clicking the arrows on the right side of the panel.

Entering a Batch file name will enable the Save and Run button.

Copy

Select this option to copy the highlighted estimation ID. The '_COPY1' value will be appended to the end of the copied estimation ID, as shown in the Estimation ID Options panel above.
Select the Estimation Mode from the options in the drop-down list. There are two options available.

Cross Validation - When you perform a Cross Validation, the results are not written to the block model. Instead, a grade estimation is performed at each sample point, while ignoring the data value at that sample point. The resulting estimates are written to a nominated mapfile for analysis. Areas where the estimated value differs significantly from the actual value may be areas that should receive extra attention. A large difference may indicate that the grade estimation process does not have enough data to provide reliable estimates.
Jackknife - Jackknife estimates bias and variance. How similar or different grades are of samples in one dataset from the nearest sample in another dataset is the basic answer sought with Jackknife. A basic condition is that both datasets are defined within the same geological domain. The first dataset may be exploration drillhole samples and the second dataset might be production blasthole samples. Alternatively, both datasets may be exploration samples with the same field grade (Au, Cu, etc.) but different drillhole type, or different drilling contractor, etc.

Select the type of Estimator you want to apply. The options will change depending on your selection of estimator.
Select the Block Model from the drop-down list. The drop-down list displays all files found in the current working directory that have the (.bmf) extension. Click Browse to select a file from another location.
Specify the name of the database or mapfile that contains the sample data. The drop-down list labelled Select Database or Map File contains all of the Vulcan database files and mapfiles found within your current working directory. Click Browse to select a file from another location.

Alternatively, you can use an ODBC link to connect to a database that contains the sample data. Click here for information about ODBC databases.
Enter the name of the Sample Group (database key) to be loaded. Wildcards (* multi-character wildcard and % single character wildcard) may be used to select multiple groups.

Note: Multiple groups only apply to Isis databases (ASCII mapfiles consist of one group).
Select the names of the fields containing the X, Y and Z coordinates from the Location field drop-down lists.
Select the field that the estimates will be calculated from using the Grade field drop-down list.
Select the Use variable weighting checkbox if you want to multiply the sample weights by the value of the specified weighting variable. The weighting variable may represent a specific gravity, sample length, or sample weight.

A block with two samples is to be estimated. The first sample has a grade value of 2 and a weight variable of 1. The second sample has a grade value of 5 and a weight variable of 2.5. The weights, from ordinary kriging, are 0.8 for the first sample and 0.2 for the second sample. Without variable weighting the estimated grade is:

(0.8 × 2 + 0.2 × 5) = 2.6

With variable weighting the estimate is:

(0.8 × 1 × 2 + 0.2 × 2.5 × 5) ÷ ( 0.8 × 1 + 0.2 × 2.5 ) = 3.15385

If the variable weighting is 0 for a block, then the default grade value is stored.
If you are using simple kriging as an estimator, you have the option to choose the source for your mean. Choose Stationary mean to enter a set mean or select Mean field use a variable from the block model.
Select the Cross validation fields you want to use. These fields are from the database that you selected above. From the drop-down list labelled Drillhole field for cross validation, select the field that holds the drillhole identification information. Then from the drop-down list labelled Name, select the data field to be examined.
In the section labelled Sample Database Manipulation you can apply the base logarithm function to all sample values. Click Apply logarithm, and then enter the constant that you want to use.

Note: All original sample values must be positive for the logarithm to be defined.

The specified logarithm constant is added to the calculated logarithm.
If you want to apply cut-offs to the grades used in the estimation, click Use cut grades. Specify a lower grade cut value (grades lower than this value are set to this value) and an upper grade cut value (grades above this value are set to this value).

Select Using Filter

Use this panel to filter your sample data by setting restrictions on samples values, triangulations used, character values within database fields, and field attributes. You can use any combination of the four filters, or not use any at all. This panel is optional.

Example: The example above shows one possible way to filter data. The filters will ignore all samples with CUT values outside of the range of 0.001 to 99999.0 and include samples with DOMINIO values of 409.

The following steps show how to set your filters.

Solid Triangulation Filter

Select the Solid Triangulation Filter checkbox to limit the data by triangulation.

Clicking the Browse icon will display the following panel. From here you can select your triangulations. All triangulations found in the current working directory will be listed in the selection panel that will be displayed.
Selecting images from the panel

Click the Browse button to search for any triangulation not found in your current working directory.

Click on the name of the file(s) you want to select. Use the icons to go to the last folder visited, go up one level, or change the way details are viewed in the window.

To highlight multiple files that are adjacent to each other in the list, hold down the Shift key and click the first and last file names in that section of the list.

To highlight multiple non-adjacent files, hold down the CTRL key while you click the file names.

Move the items to the selection list on the right side of the panel.
- Click the button to move the highlighted items to the selection list on the right.
- Click the button to remove the highlighted items from the selection list on the right.
- Click the button to move all items to the selection list on the right.
- Click the button to remove all items from the selection list on the right.
Wildcard characters can be used to limit what appears on the list. Use an * for multiple characters or a % to replace a single character.

Estimation Result Variables

Use this panel to select the grade variable you want to run estimations on, along with any additional output variables. The only variable that is required is the initial grade variable. All of the output variables are optional and not needed to run your estimations.

Jackknife

The panel will display the following options when Jackknife has been selected as an estimation mode.

To set up the Jackknife analysis, following these steps.

Select the primary variable you want to use for the estimations by selecting it from the Grade variable drop-down list.

Only valid variables will be displayed in the list.
Enter a default value for blocks that are not estimated.

Select any output variables you want to include in your estimation run. Depending on which estimation method you are using, the available output variables will change. The table below shows the entire list of output variables and the estimation methods in which they are used.

To quickly populate the table with all the variables, click the Fill output variables button.

Output Variable Type	Output Variable	Default Value
Distance to Closest Sample (Anisotropic)	<grade variable>_dist_c_an	-99.0
Distance to Closest Sample (Cartesian)	<grade variable>_dist_c_ca	-99.0
Flag when Estimated	<grade variable>_flag_variable	0.0
Grade of the Closest Sample (Anisotropic)	<grade variable>_grade_c_an	-99.0
Grade of the Closest Sample (Cartesian)	<grade variable>_grade_c_ca	-99.0
Kriging Variance	<grade variable>_variance	-99.0
Maximum Kriging Weight	<grade variable>_max_weight	-99.0
Minimum Kriging Weight	<grade variable>_minimum_weight	0.0
Number of Holes	<grade variable>_num_holes	0.0
Number of Samples	<grade variable>_num_samples	-99.0
Sample Coeff. of Variation	<grade variable>_sample_coeff	-99.0
Sample Grade Minus Estimation	<grade variable>_sample_grade_diff	-99.0
Sample Mean	<grade variable>_sample_mean	-99.0
Sample Standard Deviation	<grade variable>_sample_stddev	-99.0
Sample Variance	<grade variable>_sample_variance	-99.0
Sum of Negative Weights	<grade variable>_sum_neg_wt	-99.0
Sum of Positive Weights	<grade variable>_sum_pos_wt	-99.0
Sum of Weights	<grade variable>_sum_wt	-99.0
Weight of the Mean	<grade variable>_wt_mean	-99.0

The first column labelled Output Variable Type shows a description of the variable. This field cannot be edited.

The second column labelled Output Variable is the variable name that your block mod will use. This field can be edited if desired.

Note: The name of a variable can have a maximum of 30 alphanumeric characters. The variable, which can only be entered using lowercase characters, must start with a letter and can only contain alphanumeric characters and/or underscores, for example, variable_1.

This is followed by the Default Value. This field can also be edited.

Inverse Distance / Variography

Use this panel to enter the anisotropic weightings applied to each direction of the search axes. The panel will display different options depending on whether you are using inverse distance or kriging methods for your estimation.

Note: This panel is not available if you are using Indicator Kriging.

Follow these steps if you are using Inverse Distance.

In the space provided for Anisotropic Radii, enter the weightings for the X, Y, and Z directions. These weightings are a ratio of the lengths of the major, semi-major and minor radii. Thus the major (X) axis weighting is 1 (one), the semi-major (Y) axis weighting is the length of the major radius divided by the length of the semi-major radius, and the minor (Z) axis weighting is the length of the major axis radius divided by the length of the minor axis radius. Please note that it is possible to use equivalent ratios. That is 1:0.5:0.2 is the same as 10:5:2. The weightings are the inverse of the radii ratios.

Example: If the ratio is 1:0.5:0.2, then the weightings are 1, 2 and 5. The Distances to Samples panel (in Grade Estimation) and the New Estimation File option uses these weights for the Anisotropic distance derived from the anisotropic weights option.

If desired, you can click Normalise to calculate the anisotropic weightings normalised to the search radii. The distances used here are those entered into the Standard Major, Semi-major, and Minor axis settings found on the Search Region pane. You may still edit the weightings.

Example: If the ratio is 1:0.5:0.2, then the weightings are 1, 2 and 5. The Distances to Samples panel (in Grade Estimation) and the New Estimation File option uses these weights for the Anisotropic distance derived from the anisotropic weights option.
Enter the power to use on the inverse distance by entering the number in the Power textbox. A value of 2.0 means inverse distance squared while a value of 3.0 means inverse distance cubed, etc.

Follow these steps if you are using Simple Kriging or Ordinary Kriging.

Note: Instead of the panel being displayed like the screenshot above, you will see the options shown here instead.

Select a variogram file. This step is optional. You can choose to enter the variogram information directly into the table if you desire to do so. To select the file, use the drop-down list labelled Read variogram from file, or click the Browse button if the file is located somewhere other than your current working directory.

All the files that have a (.vrg) extension will be shown in the list.

Note: To generate a variogram file, you can use an exported file from the Data Analysis tools located in the Analyse menu.
Enter the Nugget. This represents the random variability and is the value of the variogram at distance (h) ~ 0.
Complete the table defining the variogram parameters to be used. Enter the information by typing into the space provided for each column.

Tip: If you want to use block model variables instead, enable the Use block model variables checkbox, then use the drop-down lists to populate each field. The drop-down lists will automatically display all eligible variables from the block model selected at the top of the panel.

Explanation of table columns

Structure model type

Spherical

This type is the most commonly used for ore deposits. They exhibit linear behaviour at and near the origin then rise rapidly and gradually curve off.

Exponential

This type is associated with an infinite range of influence.

The sill is reached at the specified range parameter. In release 3.2 and earlier, users were required to enter a range parameter of one-third the practical sill range. To use this model, enter the practical distance of the sill as a range parameter. For backward compatibility, see the Exponential Model 3.

Gaussian

This type exhibits parabolic behaviour at the origin and, like the spherical model, rises rapidly. The Gaussian type reaches its sill smoothly, which is different from the spherical model, which reaches the sill with a definite break. The Gaussian model is rarely used in mineral deposits of any kind. It is used most often for values that exhibit high continuity.

In release 3.2 and earlier, users were required to enter a sill range of 3 times the actual sill range. To use this model, enter the effective range of the sill. For backward compatibility, see the Gaussian model 3.

Linear

This type is a straight line with a slope angle defining the degree of continuity.

De-Wijsian

This type is a representation of a linear semi-variogram versus its logarithmic distance.

Power

This type is computed as M - d**p where M = the maximum correlation defined as 1000.0, d = distance from the origin, p = model power. For this model type only the power p is the major axis radius. Adjust the size of the ellipsoid so that the major axis is the desired power. The size of the ellipsoid for this model does not change the calculation of the variogram.

Exponential Model 3

This is an un-normalised exponential model for compatibility with release 3.2 and earlier. This variogram will have the practical sill at three times the distance entered as range parameter.

Periodic

This is a sine wave with one complete period over the effective range. This model is not commonly used because it can cause samples at greater distances to have higher correlation.

Gaussian Model 3

This is an un-normalised Gaussian model for compatibility with release 3.2 and earlier. The input radius must be the effective radius multiplied by 3.

Dampened Hole Effect

Dampening is achieved by multiplying the covariance function by an exponential covariance, that acts as a dampening function.

Sill Differential

This represents the difference between the value of the variogram where it levels off and the nugget.

If you have a total sill of 1.0, and a nugget of 0.15, you want your sill differential to be 0.85 = (1.0 - 0.15).

In the diagram, C₀is the nugget, and C is the sill differential.

Bearing/Plunge/Dip

This is the bearing (Rotation about the Z axis), plunge (rotation about the Y axis) and dip (rotation about the X axis) of the variogram.

Major/Semi-Major/Minor Axis radii

This is the radii of the major, semi-major and minor axes of the variogram.

Search Region

Use this panel to set the search direction and how far to look for samples.

Follow these steps:

Select the shape of your search area. Select Ellipsoid or Box.

The major radius is "a", the semi-major radius is "b" and the minor radius is "c".

Note: The volume of a box with sides 2a, 2b, and 2c is about twice the volume of an ellipsoid with radii a, b, and c. Therefore, when using the box search you collect about twice as many sample points. This causes an estimation using a box search to take from two to eight times as much time as an estimation with a search ellipsoid.
Set the search orientation. The Bearing, Plunge, and Dip values are angles, in degrees, that specify the orientation of the search ellipsoid and orientation of variogram structures.

Care must be taken with these parameters as there are several common misunderstandings about the meaning of these parameters.

To understand these parameters, imagine an ore body with a primary axis. To find the bearing of the ore body, project the ore body axis straight up onto the surface plane and call this line the bearing line. The bearing is the angle clockwise from north to the bearing line.

Figure 6 : Bearing

Plunge is the angle between the horizontal plane and the ore body axis. Note that the plunge should be negative for a downward pointing ore body.

Figure 7 : Plunge

To find the dip of an ore body, imagine the ore body is located in a plane. First rotate around the Z axis by the bearing so that the ore body is pointing north. Then rotate around the east-west axis by the plunge so that the ore body is level with the ground. At this point the ore body is parallel to the north-south axis. The dip is the angle of rotation to bring the plane into the horizontal plane. Looking north, if the plane must be rotated clockwise around the north-south axis, then the dip is positive (other software packages may use the opposite convention).

Figure 8 : Dip

Note: The terms bearing, plunge and dip have been used by various authors with various meanings. In this panel, as well as kriging and variography, they do not refer to true geological bearing, plunge, and dip. The terms X', Y', and Z' axis are used to denote the rotated axes as opposed to X, Y, and Z which denote the axes in their default orientation.
Enter the dimensions of the search box. The search box has sides with length twice the numbers given. The major axis radius is the search distance along the axis of the ore body. The semi-major radius is the search distance in the ore body plane perpendicular to the ore body axis. The minor axis radius is the search distance perpendicular to the ore body plane.

Note
The search radii are true radii. If you set your major search radius to '100', then the ellipsoid has a total length of 200. The following diagram shows the relationship between the axes with the ellipse in the default orientation (bearing 90°, plunge and dip 0.00°).

Figure 9 : Relationship between radii
If you are using a tetrahedral model has been created, you can select the Unfold checkbox to select a (.tetra) file from the Unfolding spec file drop-down list. This list will contain all (.tetra) files found within your current working directory. Refer to the Unfolding section for more information on tetrahedral modelling.
Click the Interactive button to display the Edit Interactive Ellipsoid panel define search ellipsoids on screen in Vulcan. Once defined in Vulcan, the parameters will then be written back into the panel.

Sample Count

Use this panel to set the minimum and maximum number of samples that will be used to estimate the grade of a block.

Follow these steps:

Enter the lowest number of samples in the box labelled Minimum number of samples per estimate.

This is the minimum number of samples that needs to be found to generate an estimate. Blocks with less than this number of samples within the search ellipsoid or search box are assigned the default grade value.
Enter the largest number of samples in the box labelled Maximum number of samples per estimate.

This is the maximum number of samples to be used in any grade estimation. Up to 999 samples per estimate are allowed.

Example: The estimation program may find 30 samples near a block centre. If you had specified a maximum of 10 samples, then only the 10 samples closest to the block centre are used. The distance to the block centre is calculated by an anisotropic distance based on the search radii.
Decide whether or not to use an octant search. The space around a block centre is divided into eight octants by three orthogonal planes.

Note: An octant search is a declustering tool used to reduce imbalance problems associated with samples lying in different directions. If there are more samples in one direction than another, then this option limits the bias.

If want to use an octant search, enable the checkbox labelled Use Octant Based Search. This places a limit on the number of samples that can come from a given octant.
Enter the maximum number of samples from each octant to be used in the estimation in the box labelled Maximum samples per octant. Samples closest to the block centre are used first.

Note: The maximum number of samples per estimate always applies, regardless of the maximum samples per octant value.

Enable the checkbox labelled Additional restrictions if you want to limit the number of samples for octants. Then enter the number of minimum and minimum samples per octant.

The minimum octants with samples enables you to specify the number of octants that must contain samples for an estimate to be generated. The minimum samples per octant enables you to specify the number of samples per octant that needs to be found to generate an estimate. These two restrictions work together. An octant is considered filled if it contains at least the minimum number of samples per octant. The minimum number of octants with samples requires that at least that number of octants be filled.

If you set the minimum number of samples per octant to 2, the minimum number of octants to 3 and have the following number of samples per octant, there are two filled octants. As this is less than the minimum number of octants with samples, the default value is assigned to this block.

Octant Number	Number of samples per octant	Filled / Not Filled
0	1	Not filled
1	3	Filled
2	2	Filled
3	1	Not filled
4	1	Not filled
5	1	Not filled
6	1	Not filled
7	0	Not filled

Enable the checkbox labelled Store octants used if you want to save the number of octants in a block model variable.
Enable the checkbox labelled Store octants information if you want to save information concerning which octants were used by each estimated block in a block model variable.

Select octant rotation type.

Rotate axes	This consists of three planes perpendicular to axes that have been rotated 45° about the Z axis and 35° about the X' (X axis after rotation about the Z axis), this produces a set of planes in which the first has a bearing of 135°, the second has a bearing of 45° and is at angle of -55° to the horizontal and the third also has a bearing of 45°, but is at an angle of 35° to the horizontal. (See the diagram below.)
Cartesian axes	This consists of three planes perpendicular to the conventional Cartesian axes X, Y, and Z (or East, North, and elevation) axes.
Ellipsoid axes	This consists of three planes that are perpendicular to the major, semi-major, and minor axes of the search ellipsoid.

The samples are sorted by distance (either anisotropic or Cartesian) prior to the samples being limited. This ensures that the closest samples are kept. Select the method by which the samples will be measured by choosing either Select by anisotropic distance or Select by Cartesian distance.
To prevent the same sample from being used more than once, enter the distance to use in Distance to check duplicate samples. Samples less than or equal to the specified distance value are considered to be duplicates, resulting in the entire grade estimation process being stopped. You can disable this feature by specifying a distance value of '-1'.

Sample Limits

Use this panel to limit the effect a high-valued sample will have on distant blocks.

Important: Using this option will not place a grade cap on the high-yield samples. It will prevent them from being used in the estimation completely.

The high-yield exclusion ellipsoid specified through this section of the Estimation Editor interface has its own major, semi-major, and minor axes that have the same orientation as the ellipsoid defined in the Search Region panel. When selecting the samples for the grade estimation, any samples within the high-yield exclusion ellipse can be chosen whether they are greater than or less than the threshold. However, between the smaller high-yield exclusion ellipse and the normal search region ellipse, only samples that are less than the threshold will be used.

Follow these steps:

Enable the checkbox labelled Exclude distant, high yield samples to ignore sample values at or above the specified threshold and outside the specified ellipsoid.
Specify the database field that contains the high yield limit. It is usually the same as the input grade field. However, other fields can be used to achieve special sample limits.

Example: You can specify a flag field here, where '0' represents an ordinary sample and '1' represents a special sample. A threshold of '0.5' would then limit the flagged samples to a smaller radius.
Enter the threshold you want to use as a limit for high-yield samples. Only samples that are less than the threshold will be used.
If you want to use a customised orientation for the search ellipsoid, enable the checkbox labelled Use angles, then enter the bearing, dip, and plunge into the spaces provided. If you do not use this option, the samples will be selected using the ellipsoid defined in the Search Region panel.

Enter the search distance into the spaces provided for Major, Semi-Major, and Minor axes radii.

Click the Interactive button to display an ellipsoid that can be edited by manipulating it with the mouse or entering the rotation and axis parameters directly.
If you want to limit how much influence a single drillhole or its samples will have, there are two methods you can apply: Limit number of samples per drillhole and Limit number of drillholes per estimate.

Note: When you select Limit number of drillholes per estimate, both the minimum and maximum number of drillholes per estimate must be specified. If you would like to apply only one of these parameters simply set the other parameter to an appropriate value. That is, if only the minimum parameter is required set the maximum to be greater than the maximum samples per estimate, or something like 99999. Similarly, if only the maximum parameter is required set the minimum to be 0 or 1.
Specify the name of the database field containing the drillhole name by selecting the field from the drop-down list labelled Field for drillhole ID. The default is DHID.

Soft Boundaries

Use this panel to setup soft boundaries. Sometimes samples that are at a different estimation domain share similar grade properties when they are located close to the limit between the domains. This is often known as a soft boundary between the domains. In this case, it could be useful to include samples from a different domain but only at short distances from the blocks in the current domain.

Follow these steps:

Select this checkbox labelled Use soft boundaries to make the rest of the panel available.
Enter or select from the Soft boundary drop-down list the variable that will be used as a criteria to identify the estimation domains. The list is populated with the names of the database fields.
If you want block model variables to be used as radii for restricted search ellipsoid or the bearing, plunge, and dip values of the restricted search region, click the option labelled Use block model variables. All the block model variables will populate the drop-down list of the respective fields.

Explanation of table headings:

Values

Click on this field or select to display the Values panel.

Enter the values associated with the selected soft boundary. This panel will differ depending on whether the current boundary has a number or character value associated with it. Samples that have the values in this list for the soft boundary variable will be forced to use the ellipsoid specified in the next six boxes.

Major/Semi/Minor axis radius

Enter the radii for the restricted search ellipsoid or select a block model variable from the drop-down list.

Bearing/Plunge/Dip

Enter the bearing, plunge, and dip of the restricted search region or select a block model variable from the drop-down list.

Note: If the sample selection criteria does not allow for samples in soft boundaries domains to be selected, then no samples will be applied to the definitions specified here.
Click the Interactive button to display the Edit Interactive Ellipsoid panel define search ellipsoids on screen in Vulcan. Once defined in Vulcan, the parameters will then be written back into the panel.

Note: Clicking on a row to highlight it will enable the Interactive button.

Validation Estimation Editor

Instructions

Sample Selection

Select Using Filter

Estimation Result Variables

Follow these steps to set up the cross validation.

To set up the Jackknife analysis, following these steps.

Inverse Distance / Variography

Follow these steps if you are using Inverse Distance.

Follow these steps if you are using Simple Kriging or Ordinary Kriging.

Explanation of table columns

Search Region

Sample Count

Sample Limits

Soft Boundaries