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rolling linear regression in q

powerpeanuts
New Contributor III

hi, is there a function to compute rolling linear regression (multiple independent variables) for a q table?

 

I am looking for something like https://www.statsmodels.org/dev/generated/statsmodels.regression.rolling.RollingOLS.html in python. Thanks.

 

pseudo code:

e.g. rlreg[n;endog;exog]

select rlreg[20;col1;(col2;col3)] from table... -> the result is a list of betas

 

1 ACCEPTED SOLUTION

BaiChen
New Contributor III

 

tData:([]y:10?100.0;x1:10?10.0;x2:10?20.0;x3:10?30.0;const:1.0)
tData
y        x1        x2        x3       const
-------------------------------------------
8.226874 2.037285  8.538354  16.01854 1    
51.32018 7.757617  15.40955  28.16125 1    
49.47829 0.6938325 0.3188056 9.083402 1    
86.65565 4.101914  7.146077  13.34548 1    
64.14975 2.337549  0.5094767 13.24347 1    
90.82711 7.125845  13.76178  21.80396 1    
97.96094 1.392257  12.75511  29.98824 1    
30.77491 2.701876  0.7691273 22.29986 1    
36.52273 6.357182  17.94471  7.113864 1    
95.91177 7.771303  15.87103  17.01243 1    

rolling:{[w;t] (w-1)_({ 1_x,y }\[w#delete from t;t])}

fn:{[t;Y;X] yx:enlist t[Y] mmu flip t[`const,X];xx:x mmu flip[x:t[`const,X]];yx lsq xx}

fn[;`y;`x1`x2`x3] each rolling[5;tData]
49.22355 4.14351 -3.200252 -0.6170487 
30.90215 9.65294 -4.097335 0.03631143 
41.24432 -5.843066 0.4397651 1.026252 
14.49142 -2.988273 -0.3123183 2.138712
6.81604 -5.333931 1.68819 1.800037    
-18.19828 -2.163089 3.582677 1.640662 
q)

 

 

 

It returns rows of lists of betas with rolling window:5 

 

View solution in original post

2 REPLIES 2

BaiChen
New Contributor III

 

tData:([]y:10?100.0;x1:10?10.0;x2:10?20.0;x3:10?30.0;const:1.0)
tData
y        x1        x2        x3       const
-------------------------------------------
8.226874 2.037285  8.538354  16.01854 1    
51.32018 7.757617  15.40955  28.16125 1    
49.47829 0.6938325 0.3188056 9.083402 1    
86.65565 4.101914  7.146077  13.34548 1    
64.14975 2.337549  0.5094767 13.24347 1    
90.82711 7.125845  13.76178  21.80396 1    
97.96094 1.392257  12.75511  29.98824 1    
30.77491 2.701876  0.7691273 22.29986 1    
36.52273 6.357182  17.94471  7.113864 1    
95.91177 7.771303  15.87103  17.01243 1    

rolling:{[w;t] (w-1)_({ 1_x,y }\[w#delete from t;t])}

fn:{[t;Y;X] yx:enlist t[Y] mmu flip t[`const,X];xx:x mmu flip[x:t[`const,X]];yx lsq xx}

fn[;`y;`x1`x2`x3] each rolling[5;tData]
49.22355 4.14351 -3.200252 -0.6170487 
30.90215 9.65294 -4.097335 0.03631143 
41.24432 -5.843066 0.4397651 1.026252 
14.49142 -2.988273 -0.3123183 2.138712
6.81604 -5.333931 1.68819 1.800037    
-18.19828 -2.163089 3.582677 1.640662 
q)

 

 

 

It returns rows of lists of betas with rolling window:5 

 

BaiChen
New Contributor III

Wrapped them into function:

tabData:([]y:10?100.0;x1:10?10.0;x2:10?20.0;x3:10?30.0;const:1.0);
main:{[n;y;xs;tab]
 rolling:{[w;t] (w-1)_({ 1_x,y }\[w#delete from t;t])};
 fn:{[t;Y;X] yx:enlist t[Y] mmu flip t[`const,X];xx:x mmu flip[x:t[`const,X]];yx lsq xx};
 fn[;y;xs] each rolling[n;tab]
 }

betas:main[5;`y;`x1`x2`x3;tabData]