item[i], Julia has to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

item[i], Julia has to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

item[i], Julia has to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

item[i], Julia has to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

item[i], Julia has to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

PERFORMANCE TIPS 474 to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

PERFORMANCE TIPS 474 to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

PERFORMANCE TIPS 474 to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

PERFORMANCE TIPS 475 to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods

PERFORMANCE TIPS 474 to look up the type at run-time, search for the appropriate method in method tables, decide (via type intersection) which one matches, determine whether it has been JIT-compiled yet Generalized linear models are provided by the GLM package. • Julia provides tuples and real hash tables, but not R-style lists. When returning multiple items, you should typically use a tuple or a named static dispatch, i.e. you need to annotate a function as virtual, in order to have dynamic dispatch. On the other hand, in Julia every method is "virtual" (although it's more general than that since methods