Description Usage Arguments Details Value Examples
Outputs coefficients of the linear model fitted to Aster table according
to the formula expression containing column names. The zeroth coefficient corresponds
to the slope intercept. R formula expression with column names for response and
predictor variables is exactly as in lm
function (though less
features supported).
1 2 
channel 
connection object as returned by 
tableName 
Aster table name 
formula 
an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under 'Details'. 
tableInfo 
prebuilt table summary with data types 
categories 
vector with column names containing categorical data. Optional if the column is of character type as it is automatically treated as categorical predictors. But if numerical column contains categorical data then then it has to be specified for a model to view it as categorical. Apply extra care not to have columns with too many values (approximaltely > 10) as categorical because each value results in dummy predictor variable added to the model. 
sampleSize 
function always computes regression model coefficent on all data in the table.
But it computes predictions and returns an object of 
where 
specifies criteria to satisfy by the table rows before applying
computation. The creteria are expressed in the form of SQL predicates (inside

test 
logical: if TRUE show what would be done, only (similar to parameter 
Models for computeLm
are specified symbolically. A typical model has the form
response ~ terms
where response is the (numeric) column and terms is a series of
column terms which specifies a linear predictor for response. A terms specification of
the form first + second
indicates all the terms in first together with all the
terms in second with duplicates removed. A specification of the form first:second
and first*second
(interactions) are not supported yet.
computeLm
returns an object of class
"toalm", "lm"
.
The function summary
.....
For backward compatibility Outputs data frame containing 3 columns:
name of predictor table column, zeroth coefficient name is "0"
index of predictor table column starting with 0
coefficient value
1 2 3 4 5 6 7 8 9 10 11 12 13 14  if(interactive()){
# initialize connection to Lahman baseball database in Aster
conn = odbcDriverConnect(connection="driver={Aster ODBC Driver};
server=<dbhost>;port=2406;database=<dbname>;uid=<user>;pwd=<pw>")
# batting average explained by rbi, bb, so
lm1 = computeLm(channel=conn, tableName="batting_enh", formula= ba ~ rbi + bb + so)
summary(lm1)
# with category predictor league and explicit sample size
lm2 = computeLm(channel=conn, tableName="batting_enh", formula= ba ~ rbi + bb + so + lgid,
, sampleSize=10000, where="lgid in ('AL','NL') and ab > 30")
summary(lm2)
}

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