arma regression with NAN

HI,the two matrix are included as attached . rows represent time series. how to conduct arma model( inc. error and intercept term)with return(t) as y and MAprice(t-1) as explanary variable. The output of the coefficients of x should be in a matrix B which has the corresponding row and column as the return matrix. NOTE, the regression is only done with the MAprice available values. So some values in return matrix will be kicked due to the 1 to 1 relationship between y and x.

return=0  0  0  0  0  0  0  0  0  0
0.448154165  -6.968325792  -3.280941338  0.479237811  9.547738693  11.73457986  5.428571429  5.424485939  0  -3.101851852
6.251742792  -2.399481193  -6.353787408  -7.654081225  9.174311927  -4.56630137  10.56910569  -11.5759843  0  -1.672240803
14.28721394  20.06644518  9.501683182  24.35207521  15.12605042  27.75131842  17.64705882  20.72749816  0  16.69073737
6.980802792  0.249031544  2.065382117  10.66599682  2.99270073  1.87258427  -0.625  -4.216917632  0  7.231068369
0.413187945  -2.658937345  -2.630697438  -2.662218288  -4.676258993  -3.676326233  -7.446808511  -11.95004093  0  -5.140896839
-24.64984776  -21.56069364  -13.61064591  -11.32717777  -26.41509434  -11.45037294  -17.70114943  -19.2853264  0  -12.77123373
-11.45875426  -23.87619749  -11.2490831  -15.85853274  -21.02564103  -6.03464997  -14.80446927  -17.69946687  0  -10.22269604
-3.761898553  9.825750242  -1.40504162  6.806462702  5.194805195  -31.19259742  3.278688525  0.806781361  0  14.46101069
-16.48262313  -9.211106214  -6.28704868  2.94057407  -3.703703704  4  -11.9047619  -2.197468354  0  -0.806916427
7.916937054  -2.718446602  -10.06325474  5.713148769  3.846153846  -4.615384615  0.900900901  0.561710499  -3.225968494  2.167344567
-2.525556224  -0.598802395  4.745666382  1.352441385  0.617283951  -2.419354839  -17.14285714  -10.05559989  -4.666493641  0.534607291
26.41887724  20.73293173  16.83396636  -0.888712031  20.24539877  19.00826446  22.84482759  20.49653001  6.293150387  8.174463993
1.951933634  1.912681913  -1.387437594  0  15.81632653  11.11111111  -1.052631579  -9.278105666  -4.605108136  6.343478716
-2.297475171  -0.611995104  11.5146877  -1.346359743  -2.202643172  -3.125  -0.709219858  -3.409864391  6.207444638  4.357019916
-3.135333742  8.210180624  -2.265258935  7.274059202  -1.801801802  11.61290323  10.71428571  -7.059126452  0.649006006  6.9223882
-0.202301176  -2.921092564  -7.295383744  -5.254226314  -9.174311927  -0.115606936  -0.967741935  2.532734537  -6.000519076  -2.088047598
2.130039275  1.953888238  11.37044052  0.904794058  0.518134715  1.183431953  6  10.00014221  -2.127119112  4.660670482
2.238900903  13.45343043  0  4.483404711  -12.06185567  -11.11111111  -3.459119497  -9.652105338  -2.174477257  0
-1.990792584  -4.155405405  -0.526662278  -6.43781222  0.82063306  -2.631578947  -5.537459283  -1.864491665  -7.406681124  0
MAprice=NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN
NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN
0.959374344  1.041971207  1.057307224  1.053534979  0.917366947  0.995216263  0.920751634  1.067879722  NaN  1.022189828
0.899497872  0.895406752  0.962805802  0.891663351  0.888077859  0.867665169  0.872916667  0.921687137  NaN  0.915041954
0.917546722  0.942773024  0.958170711  0.882133103  0.947242206  0.91666685  0.963120567  0.969601472  NaN  0.913142204
0.98677686  1.030539499  1.037432671  0.988287322  1.027672956  1.019083192  1.061302682  1.107146187  NaN  1.012433698
1.223941196  1.203267011  1.130863809  1.095442195  1.261538462  1.100574051  1.175977654  1.215336888  NaN  1.118317144
1.209436259  1.329461116  1.143672393  1.176255508  1.329004329  1.08868632  1.2  1.240144834  NaN  1.130272243
1.07088499  1.035551638  1.052352155  1.016336523  1.051440329  1.333333333  1.034920635  1.087911392  NaN  0.948933718
1.14717175  1.034789644  1.049794475  0.960320618  1.008547009  1.119657692  1.078078078  1.02246842  NaN  0.962967267
1.012051513  1.053393214  1.099460074  0.954963433  0.987654321  1.018817204  1.038690476  1.00372382  NaN  0.988511631
0.992185893  1.013386881  1.005403328  0.973329796  0.983640082  1.033057851  1.13433908  1.072461902  1.044288359  0.989421282
0.867512505  0.887179487  0.891017454  1.001490007  0.886054422  0.900462963  0.932163743  0.91752663  0.975879956  0.947983126
0.918910295  0.931320549  0.960675811  1.002988936  0.860499266  0.885416667  0.944444444  1.005680926  1.01149487  0.936546185
1.009144723  0.997810619  0.935367506  1.009098226  0.968468468  0.987096774  1.008333333  1.058828312  0.976186624  0.953112483
1.029670839  0.951315124  1.011705843  0.95903519  1.019877676  0.94026975  0.937634409  1.063296492  0.997778355  0.943822536
1.012162676  0.994008076  1.078694935  1.021111861  NaN  0.980276134  0.988888889  1.008224425  1.052014652  0.9982284
1.003392274  0.997061454  0.955489723  1.016443612  NaN  1  0.972746331  0.931907797  1.036230003  0.980092593
0.986728049  0.915315315  0.965968108  0.968532514  NaN  1.078947368  1.004343105  1.037680952  1.022224273  NaN
1.00609369  0.987663024  1.003529671  1.030584305  NaN  1.060810811  1.051724138  1.048953564  1.061329745  NaN