maLoess package:marray R Documentation _S_t_r_a_t_i_f_i_e_d _u_n_i_v_a_r_i_a_t_e _r_o_b_u_s_t _l_o_c_a_l _r_e_g_r_e_s_s_i_o_n _D_e_s_c_r_i_p_t_i_o_n: This function performs robust local regression of a variable 'y' on predictor variable 'x', separately within values of a third variable 'z'. It is used by 'maNormLoess' for intensity dependent location normalization. _U_s_a_g_e: maLoess(x, y, z, w=NULL, subset=TRUE, span=0.4, ...) _A_r_g_u_m_e_n_t_s: x: A numeric vector of predictor variables. y: A numeric vector of responses. z: Variables used to stratify the data. w: An optional numeric vector of weights. subset: A "logical" or "numeric" vector indicating the subset of points used to compute the fits. span: The argument 'span' which controls the degree of smoothing in the 'loess' function. ...: Misc arguments _D_e_t_a_i_l_s: 'y' is regressed on 'x', separately within values of 'z' using the 'loess' function. _V_a_l_u_e: A numeric vector of fitted values. _A_u_t_h_o_r(_s): Sandrine Dudoit, . _R_e_f_e_r_e_n_c_e_s: S. Dudoit and Y. H. Yang. (2002). Bioconductor R packages for exploratory analysis and normalization of cDNA microarray data. In G. Parmigiani, E. S. Garrett, R. A. Irizarry and S. L. Zeger, editors, _The Analysis of Gene Expression Data: Methods and Software_, Springer, New York. Y. H. Yang, S. Dudoit, P. Luu, and T. P. Speed (2001). Normalization for cDNA microarray data. In M. L. Bittner, Y. Chen, A. N. Dorsel, and E. R. Dougherty (eds), _Microarrays: Optical Technologies and Informatics_, Vol. 4266 of _Proceedings of SPIE_. Y. H. Yang, S. Dudoit, P. Luu, D. M. Lin, V. Peng, J. Ngai, and T. P. Speed (2002). Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. _Nucleic Acids Research_, Vol. 30, No. 4. _S_e_e _A_l_s_o: 'maNormMain', 'maNormLoess', 'loess'. _E_x_a_m_p_l_e_s: # See examples for maNormMain.